Train

Setup

from katlas.core import *
import pandas as pd
import joblib
# from sklearn import set_config
# set_config(transform_output='pandas')

df = Data.get_ks_unique()

df

	site_seq	site_source_all	substrate_gene	sub_site	O00141_SGK1	O00238_BMPR1B	O00311_CDC7	O00329_PIK3CD	O00418_EEF2K	O00443_PIK3C2A	...	Q9Y2K2_SIK3	Q9Y2U5_MAP3K2	Q9Y3S1_WNK2	Q9Y463_DYRK1B	Q9Y4K4_MAP4K5	Q9Y572_RIPK3	Q9Y5S2_CDC42BPB	Q9Y6E0_STK24	Q9Y6M4_CSNK1G3	Q9Y6R4_MAP3K4
0	AAAAAAAAAVAAPPTAVGSLsGAEGVPVSsQPLPSQPW___	SIGNOR|human_phosphoproteome|PSP|iPTMNet	MAZ	P56270_S460	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
1	AAAAAAASGGAQQRsHHAPMsPGssGGGGQPLARtPQPssP	PSP|human_phosphoproteome|EPSD|Sugiyama	ARID1A	O14497_S363	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
2	AAAAAAAVtAAstsYYGRDRsPLRRATAPVPTVGEGYGYGH	human_phosphoproteome|PSP|EPSD	RBM4	Q9BWF3_S309	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
3	AAAAAVSRRRKAEYPRRRRssPsARPPDVPGQQPQAAKsPs	human_phosphoproteome|Sugiyama	ZFP91	Q96JP5_S83	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
4	AAAAGAGKAEELHyPLGERRsDyDREALLGVQEDVDEyVKL	Sugiyama	RCN2	Q14257_S37	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
29151	___________________MstVHEILCKLsLEGDHstPPs	SIGNOR|human_phosphoproteome|EPSD	ANXA2	P07355_S2	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
29152	___________________MsYRRELEKyRDLDEDEILGAL	human_phosphoproteome|PSP|EPSD	TMOD1	P28289_S2	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
29153	___________________MtAKMETtFYDDALNASFLPSE	SIGNOR|human_phosphoproteome|EPSD|PSP|GPS6	JUN	P05412_T2	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
29154	___________________MtSSyGHVLERQPALGGRLDsP	Sugiyama	PRRX1	P54821_T2	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
29155	___________________MttsQKHRDFVAEPMGEKPVGS	SIGNOR|human_phosphoproteome|EPSD|PSP|GPS6	BANF1	O75531_T2	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0

29156 rows × 459 columns

onehot_encode??

Signature: onehot_encode(sequences, transform_colname=True, n=20)
Docstring: <no docstring>
Source:   
def onehot_encode(sequences, transform_colname=True, n=20):
    encoder = OneHotEncoder(handle_unknown='ignore', sparse_output=False)
    encoded_array = encoder.fit_transform([list(seq) for seq in sequences])
    colnames = [x[1:] for x in encoder.get_feature_names_out()]
    if transform_colname:
        colnames = [f"{int(item.split('_', 1)[0]) - 20}{item.split('_', 1)[1]}" for item in colnames]
    encoded_df = pd.DataFrame(encoded_array, columns=colnames)
    return encoded_df
File:      ~/katlas/katlas/core.py
Type:      function

X = onehot_encode(df['site_seq'])

X

	-20A	-20C	-20D	-20E	-20F	-20G	-20H	-20I	-20K	-20L	...	20R	20S	20T	20V	20W	20Y	20_	20s	20t	20y
0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0
1	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
2	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
3	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0
4	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
29151	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0
29152	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
29153	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
29154	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
29155	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0

29156 rows × 962 columns

kinase_cols = df.columns[4:] 
data=(df[kinase_cols]>0).astype(int)

(data.sum()>50).value_counts()

True     320
False    135
Name: count, dtype: int64

Y=data.loc[:,data.sum()>50] # filter out kinases with less than 50 known substrates

from sklearn.model_selection import train_test_split

X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2, random_state=42)

# Wrap XGBClassifier with MultiOutputClassifier
model = MultiOutputClassifier(xgb.XGBClassifier(use_label_encoder=False, eval_metric='logloss'))
model.fit(X_train, Y_train)

/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:03] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:04] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:06] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:08] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:09] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:11] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:12] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:14] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:16] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:17] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:19] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:20] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:22] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:23] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:25] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:26] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:28] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:29] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:31] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:32] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:33] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:35] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:36] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:38] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:39] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:41] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:42] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:44] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:45] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:47] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:49] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:50] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:52] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:53] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:55] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:56] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:58] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:40:59] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:00] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:02] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:03] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:05] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:06] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:08] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:09] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:11] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:12] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:14] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:15] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:16] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:18] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:19] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:21] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:22] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:24] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:25] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:27] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:28] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:30] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:31] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:33] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:35] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:36] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:38] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:39] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:41] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:42] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:43] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:45] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:46] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:48] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:49] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:51] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:52] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:54] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:55] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:56] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:58] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:41:59] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:01] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:02] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:04] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:05] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:06] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:08] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:09] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:11] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:12] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:14] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:15] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:17] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:18] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:20] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:22] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:24] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:25] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:27] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:28] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:29] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:31] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:32] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:34] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:35] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:37] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:38] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:39] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:41] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:42] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:44] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:45] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:47] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:48] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:49] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:51] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:52] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:54] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:55] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:56] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:58] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:42:59] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:01] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:03] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:04] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:06] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:07] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:09] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:10] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:12] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:13] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:15] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:16] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:17] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:19] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:20] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:22] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:23] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:25] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:26] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:27] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:29] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:30] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:32] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:33] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:34] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:36] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:37] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:39] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:40] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:42] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:43] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:44] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:46] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:47] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:49] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:51] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:52] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:54] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:56] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:57] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:43:59] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:00] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:01] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:03] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:04] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:06] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:07] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:09] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:10] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:11] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:13] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:14] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:16] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:17] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:19] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:20] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:21] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:23] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:24] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:26] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:27] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:29] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:30] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:32] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:33] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:34] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:36] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:37] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:40] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:41] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:42] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:44] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:45] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:47] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:48] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:50] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:51] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:52] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:54] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:55] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:57] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:44:58] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:00] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:01] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:02] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:04] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:05] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:07] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:08] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:10] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:11] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:12] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:14] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:15] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:17] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:18] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:20] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:21] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:22] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:24] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:25] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:27] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:29] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:31] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:32] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:33] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:35] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:36] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:38] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:39] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:41] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:42] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:43] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:45] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:46] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:48] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:49] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:50] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:52] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:53] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:55] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:56] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:58] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:45:59] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:00] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:02] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:03] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:05] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:06] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:07] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:09] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:10] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:12] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:14] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:16] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:17] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:19] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:21] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:22] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:24] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:25] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:26] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:28] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:29] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:31] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:32] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:34] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:35] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:36] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:38] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:39] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:41] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:42] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:44] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:45] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:46] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:48] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:49] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:51] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:52] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:54] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:55] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:57] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:46:59] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:01] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:02] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:03] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:05] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:06] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:08] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:09] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:11] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:12] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:13] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:15] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:16] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:18] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:19] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:20] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:22] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:23] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:25] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:26] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:28] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:29] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:30] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:32] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:33] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:35] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:36] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:38] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:39] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:41] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:42] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:44] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:46] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:47] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:49] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:50] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:51] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:47:53] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
Cell In[103], line 7
      5 # Compute SHAP values for each label
      6 for i, estimator in enumerate(model.estimators_):
----> 7     explainer = shap.Explainer(estimator, X_train)
      8     shap_values = explainer(X_test)
      9     if i ==10: break

NameError: name 'shap' is not defined

joblib.dump(model, 'multioutput_xgb_model.pkl')

['multioutput_xgb_model.pkl']

model = joblib.load('multioutput_xgb_model.pkl')

import shap

explainer = shap.TreeExplainer(model.estimators_[46])

shap_values = explainer.shap_values(X)

shap_values.shape

(29156, 962)

shap_df = pd.DataFrame(shap_values,index=X.index,columns=X.columns)

df.columns[df.columns.str.contains('CDK1')]

Index(['O94921_CDK14', 'P06493_CDK1', 'P21127_CDK11B', 'Q00536_CDK16',
       'Q07002_CDK18', 'Q14004_CDK13', 'Q15131_CDK10', 'Q96Q40_CDK15',
       'Q9BWU1_CDK19', 'Q9NYV4_CDK12', 'Q9UQ88_CDK11A'],
      dtype='object')

colname = 'P06493_CDK1'

get_prob??

Signature:
get_prob(
    df: pandas.core.frame.DataFrame,
    col: str,
    aa_order=['P', 'G', 'A', 'C', 'S', 'T', 'V', 'I', 'L', 'M', 'F', 'Y', 'W', 'H', 'K', 'R', 'Q', 'N', 'D', 'E', 's', 't', 'y'],
)
Source:   
def get_prob(df: pd.DataFrame, col: str, aa_order=[i for i in 'PGACSTVILMFYWHKRQNDEsty']):
    """Get the probability matrix of PSSM from phosphorylation site sequences."""
    
    site = check_seq_df(df, col)
    
    site_array = np.array(site.apply(list).tolist())
    seq_len = site_array.shape[1]
    
    position = list(range(-(seq_len // 2), (seq_len // 2)+1)) # add 1 because range do not include the final num
    
    site_df = pd.DataFrame(site_array, columns=position)
    melted = site_df.melt(var_name='Position', value_name='aa')
    
    grouped = melted.groupby(['Position', 'aa']).size().reset_index(name='Count')
    grouped = grouped[grouped.aa.isin(aa_order)].reset_index(drop=True)
    
    pivot_df = grouped.pivot(index='aa', columns='Position', values='Count').fillna(0)
    pssm_df = pivot_df / pivot_df.sum()
    
    pssm_df = pssm_df.reindex(index=aa_order, columns=position, fill_value=0)
    pssm_df = pssm_df.rename(index={'s': 'pS', 't': 'pT', 'y': 'pY'})
    
    return pssm_df
File:      ~/katlas/katlas/core.py
Type:      function

idxs = df.index[df[colname]==1]

flat_pssm = shap_df.iloc[idxs].mean()

flat_pssm_1 = (X*shap_df).mean()
flat_pssm_0 = ((1-X)*shap_df).mean()

pssm_1 = recover_pssm(flat_pssm_1)
pssm_0 = recover_pssm(flat_pssm_0)

from katlas.plot import *

plot_heatmap(pssm_0,figsize=(14,7))

plot_heatmap(pssm_1,figsize=(14,7))

recover_pssm?

Signature: recover_pssm(flat_pssm: pandas.core.series.Series)
Docstring: Recover 2D pssm from flat pssm Series
File:      ~/katlas/katlas/core.py
Type:      function

X.shape

(29156, 962)

shap.force_plot?

Signature:
shap.force_plot(
    base_value,
    shap_values=None,
    features=None,
    feature_names=None,
    out_names=None,
    link='identity',
    plot_cmap='RdBu',
    matplotlib=False,
    show=True,
    figsize=(20, 3),
    ordering_keys=None,
    ordering_keys_time_format=None,
    text_rotation=0,
    contribution_threshold=0.05,
)
Docstring:
Visualize the given SHAP values with an additive force layout.
Parameters
----------
base_value : float or shap.Explanation
    If a float is passed in, this is the reference value that the feature contributions start from.
    For SHAP values, it should be the value of ``explainer.expected_value``.
    However, it is recommended to pass in a SHAP :class:`.Explanation` object instead (``shap_values``
    is not necessary in this case).
shap_values : numpy.array
    Matrix of SHAP values (# features) or (# samples x # features). If this is a
    1D array, then a single force plot will be drawn. If it is a 2D array, then a
    stacked force plot will be drawn.
features : numpy.array
    Matrix of feature values (# features) or (# samples x # features). This provides the values of all the
    features, and should be the same shape as the ``shap_values`` argument.
feature_names : list
    List of feature names (# features).
out_names : str
    The name of the output of the model (plural to support multi-output plotting in the future).
link : "identity" or "logit"
    The transformation used when drawing the tick mark labels. Using "logit" will change log-odds numbers
    into probabilities.
plot_cmap : str or list[str]
    Color map to use. It can be a string (defaults to ``RdBu``) or a list of hex color strings.
matplotlib : bool
    Whether to use the default Javascript output, or the (less developed) matplotlib output.
    Using matplotlib can be helpful in scenarios where rendering Javascript/HTML
    is inconvenient. Defaults to False.
show : bool
    Whether :external+mpl:func:`matplotlib.pyplot.show()` is called before returning.
    Setting this to ``False`` allows the plot
    to be customized further after it has been created.
    Only applicable when ``matplotlib`` is set to True.
figsize :
    Figure size of the matplotlib output.
contribution_threshold : float
    Controls the feature names/values that are displayed on force plot.
    Only features that the magnitude of their shap value is larger than min_perc * (sum of all abs shap values)
    will be displayed.
File:      /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/shap/plots/_force.py
Type:      function

shap.force_plot(explainer.expected_value, shap_values[0],X_train.iloc[0],matplotlib=True)

shap.summary_plot(shap_values, X, plot_type="bar")

shap.summary_plot(shap_values, X)

explainer.expected_value

-3.6888542

explainer = shap.Explainer(model.estimators_[46], X_train)
shap_test = explainer(X_test)
# shap_train = explainer(X_train)

shap_test

.values =
array([[ 0.00206763,  0.        , -0.00956931, ...,  0.00070516,
         0.        ,  0.        ],
       [ 0.00206763,  0.        ,  0.00141108, ...,  0.00027887,
         0.        ,  0.        ],
       [ 0.00206763,  0.        ,  0.00188144, ...,  0.00070516,
         0.        ,  0.        ],
       ...,
       [ 0.00206763,  0.        ,  0.00188144, ...,  0.00070516,
         0.        ,  0.        ],
       [ 0.00581243,  0.        ,  0.00188144, ...,  0.00070516,
         0.        ,  0.        ],
       [ 0.00206763,  0.        ,  0.00188144, ...,  0.00070516,
         0.        ,  0.        ]])

.base_values =
array([-5.57500997, -5.57500997, -5.57500997, ..., -5.57500997,
       -5.57500997, -5.57500997])

.data =
array([[0., 0., 0., ..., 0., 0., 0.],
       [0., 0., 0., ..., 0., 0., 0.],
       [0., 0., 0., ..., 0., 0., 0.],
       ...,
       [0., 0., 0., ..., 0., 0., 0.],
       [0., 0., 0., ..., 0., 0., 0.],
       [0., 0., 0., ..., 0., 0., 0.]])

import shap

# Compute SHAP values for each label
for i, estimator in enumerate(model.estimators_):
    explainer = shap.Explainer(estimator, X_train)
    shap_values = explainer(X_test)
    if i ==10: break

shap_df = pd.DataFrame(
    shap_values.values,
    columns=X_test.columns,
    index=X_test.index
)

Y_test.iloc[:,10][Y_test.iloc[:,10]==1]

16979    1
14709    1
2275     1
8769     1
27218    1
        ..
20779    1
960      1
7986     1
2554     1
23184    1
Name: O15111_CHUK, Length: 98, dtype: int64

shap_df

	-20A	-20C	-20D	-20E	-20F	-20G	-20H	-20I	-20K	-20L	...	20R	20S	20T	20V	20W	20Y	20_	20s	20t	20y
16025	-0.001766	0.0	0.0	-0.008262	0.0	0.000000	-0.007991	0.0	0.0	0.015426	...	0.008585	0.043172	0.005846	-0.008903	0.0	0.0	0.0	0.000000	0.0	-0.012251
15040	-0.010175	0.0	0.0	0.000000	0.0	0.000000	-0.002976	0.0	0.0	-0.278704	...	0.009266	0.089959	0.004836	-0.045084	0.0	0.0	0.0	0.000000	0.0	-0.010704
19178	-0.001143	0.0	0.0	0.000000	0.0	0.000000	-0.003325	0.0	0.0	0.010434	...	0.003524	0.075065	0.001692	0.046648	0.0	0.0	0.0	0.000000	0.0	-0.010476
17659	-0.001766	0.0	0.0	0.000000	0.0	0.000000	-0.007991	0.0	0.0	0.015426	...	-0.000838	0.091592	0.005846	-0.010654	0.0	0.0	0.0	0.010562	0.0	-0.010916
16145	-0.010175	0.0	0.0	0.000000	0.0	0.000000	-0.012346	0.0	0.0	0.015426	...	-0.001271	0.083283	0.005846	-0.045084	0.0	0.0	0.0	0.000000	0.0	-0.012832
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
8663	-0.001088	0.0	0.0	0.000000	0.0	0.328290	-0.007991	0.0	0.0	0.011210	...	0.009266	0.033781	0.005846	-0.011177	0.0	0.0	0.0	0.000000	0.0	-0.012008
24778	-0.001766	0.0	0.0	0.000000	0.0	0.000000	-0.007991	0.0	0.0	0.011116	...	0.009266	0.083086	0.005846	-0.010364	0.0	0.0	0.0	0.000000	0.0	-0.012143
16483	-0.001766	0.0	0.0	0.000000	0.0	0.000000	-0.007991	0.0	0.0	0.010868	...	-0.003765	0.091999	0.005846	-0.011055	0.0	0.0	0.0	0.000000	0.0	-0.011432
24180	-0.002254	0.0	0.0	0.000000	0.0	0.000000	-0.007991	0.0	0.0	0.015426	...	0.003901	0.092182	0.005846	0.436673	0.0	0.0	0.0	0.000000	0.0	-0.011381
8200	-0.001766	0.0	0.0	0.000000	0.0	0.021635	-0.007991	0.0	0.0	0.011210	...	-0.000513	0.070115	0.002152	-0.012110	0.0	0.0	0.0	0.000000	0.0	-0.012159

5832 rows × 962 columns

Y_train.iloc[:,10]

22535    0
20205    0
6352     0
5638     0
2075     0
        ..
21575    0
5390     0
860      0
15795    0
23654    0
Name: O15111_CHUK, Length: 23324, dtype: int64

shap_values

.values =
array([[-0.00176575,  0.        ,  0.        , ...,  0.        ,
         0.        , -0.01225108],
       [-0.01017473,  0.        ,  0.        , ...,  0.        ,
         0.        , -0.01070447],
       [-0.00114341,  0.        ,  0.        , ...,  0.        ,
         0.        , -0.01047641],
       ...,
       [-0.00176575,  0.        ,  0.        , ...,  0.        ,
         0.        , -0.01143211],
       [-0.00225384,  0.        ,  0.        , ...,  0.        ,
         0.        , -0.01138087],
       [-0.00176575,  0.        ,  0.        , ...,  0.        ,
         0.        , -0.01215919]])

.base_values =
array([-6.18386969, -6.18386969, -6.18386969, ..., -6.18386969,
       -6.18386969, -6.18386969])

.data =
array([[0., 0., 0., ..., 0., 0., 0.],
       [0., 0., 0., ..., 0., 0., 0.],
       [0., 0., 0., ..., 0., 0., 0.],
       ...,
       [0., 0., 0., ..., 0., 0., 0.],
       [0., 0., 0., ..., 0., 0., 0.],
       [0., 0., 0., ..., 0., 0., 0.]])

X_test

	-20A	-20C	-20D	-20E	-20F	-20G	-20H	-20I	-20K	-20L	...	20R	20S	20T	20V	20W	20Y	20_	20s	20t	20y
16025	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
15040	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
19178	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0
17659	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0
16145	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
8663	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
24778	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
16483	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0
24180	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0
8200	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0

5832 rows × 962 columns

shap.summary_plot(shap_values, X_test, show=False)
plt.title(f'SHAP Summary for Label {i}')
plt.show()

import xgboost as xgb

# Initialize the classifier
model = xgb.XGBClassifier(objective='binary:logistic', eval_metric='logloss', use_label_encoder=False)

# Fit the model on multi-label data
model.fit(X_train, Y_train)

/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/xgboost/training.py:183: UserWarning: [01:33:06] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)

XGBClassifier(base_score=None, booster=None, callbacks=None,
              colsample_bylevel=None, colsample_bynode=None,
              colsample_bytree=None, device=None, early_stopping_rounds=None,
              enable_categorical=False, eval_metric='logloss',
              feature_types=None, feature_weights=None, gamma=None,
              grow_policy=None, importance_type=None,
              interaction_constraints=None, learning_rate=None, max_bin=None,
              max_cat_threshold=None, max_cat_to_onehot=None,
              max_delta_step=None, max_depth=None, max_leaves=None,
              min_child_weight=None, missing=nan, monotone_constraints=None,
              multi_strategy=None, n_estimators=None, n_jobs=None,
              num_parallel_tree=None, ...)

In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.

for i, estimator in enumerate(model.estimators_):
    # Compute SHAP values for label i
    explainer = shap.Explainer(estimator, X_train)
    shap_values = explainer(X_test)

    # Visualize SHAP values for label i
    shap.plots.beeswarm(shap_values, max_display=10)
    if i ==10: break

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In[100], line 1
----> 1 for i, estimator in enumerate(model.estimators_):
      2     # Compute SHAP values for label i
      3     explainer = shap.Explainer(estimator, X_train)
      4     shap_values = explainer(X_test)

AttributeError: 'XGBClassifier' object has no attribute 'estimators_'

import shap

# Create a SHAP explainer
explainer = shap.Explainer(model, X_train)

# Compute SHAP values for the test set
shap_values = explainer(X_test)

---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
Cell In[99], line 1
----> 1 import shap
      3 # Create a SHAP explainer
      4 explainer = shap.Explainer(model, X_train)

ModuleNotFoundError: No module named 'shap'

shap.summary_plot(shap_values, X_test)

shap.dependence_plot("feature_name", shap_values.values, X_test)

shap.force_plot(explainer.expected_value, shap_values.values[0], X_test[0])

from sklearn.metrics import hamming_loss, accuracy_score, f1_score

# Predict on the test set
Y_pred = model.predict(X_test)

# Compute evaluation metrics
print("Hamming Loss:", hamming_loss(Y_test, Y_pred))
print("Subset Accuracy:", accuracy_score(Y_test, Y_pred))
print("F1 Score (Micro):", f1_score(Y_test, Y_pred, average='micro'))

from sklearn.multioutput import MultiOutputClassifier
from sklearn.neighbors import KNeighborsClassifier
from sklearn.linear_model import LogisticRegression

base = KNeighborsClassifier(n_neighbors=5,n_jobs=-1)
# base = LogisticRegression(max_iter=1000)
clf = MultiOutputClassifier(base)
clf.fit(X_train, Y_train)

MultiOutputClassifier(estimator=KNeighborsClassifier(n_jobs=-1))

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Y_pred = clf.predict(X_test)
# Y_pred = clf.predict_proba(X_test)

out = pd.DataFrame(Y_pred)

from sklearn.metrics import multilabel_confusion_matrix

Y_pred

array([[0, 0, 0, ..., 0, 0, 0],
       [0, 0, 0, ..., 0, 0, 0],
       [0, 0, 0, ..., 0, 0, 0],
       ...,
       [0, 0, 0, ..., 0, 0, 0],
       [0, 0, 0, ..., 0, 0, 0],
       [0, 0, 0, ..., 0, 0, 0]])

cm = multilabel_confusion_matrix(Y_test.values, Y_pred)

import seaborn as sns

for i in range(num_classes):
    plt.figure(figsize=(4, 4))
    c_matrix = cm[i]
    plt.imshow(c_matrix, interpolation='nearest', cmap=plt.cm.Blues)
    plt.title(f'Confusion Matrix for {class_names[i]}')
    plt.xticks([0, 1], ['Predicted 0', 'Predicted 1'])
    plt.yticks([0, 1], ['Actual 0', 'Actual 1'])

    for j in range(2):
        for k in range(2):
            plt.text(k, j, format(c_matrix[j, k], 'd'),
                     ha="center", va="center",
                     color="white" if c_matrix[j, k] > c_matrix.max() / 2. else "black")

    plt.tight_layout()
    plt.show()
    if i==20: break

import matplotlib.pyplot as plt
import numpy as np

# Assuming 'cm' is your multilabel confusion matrix
num_classes = cm.shape[0]
class_names = [f'Class {i}' for i in range(num_classes)]  # Replace with actual class names if available

fig, axes = plt.subplots(nrows=1, ncols=num_classes, figsize=(5 * num_classes, 4))

for i in range(num_classes):
    ax = axes[i] if num_classes > 1 else axes
    c_matrix = cm[i]
    im = ax.imshow(c_matrix, interpolation='nearest', cmap=plt.cm.Blues)
    ax.set_title(f'Confusion Matrix for {class_names[i]}')
    ax.set_xticks([0, 1])
    ax.set_yticks([0, 1])
    ax.set_xticklabels(['Predicted 0', 'Predicted 1'])
    ax.set_yticklabels(['Actual 0', 'Actual 1'])

    # Loop over data dimensions and create text annotations.
    for j in range(2):
        for k in range(2):
            ax.text(k, j, format(c_matrix[j, k], 'd'),
                    ha="center", va="center",
                    color="white" if c_matrix[j, k] > c_matrix.max() / 2. else "black")
            break

plt.tight_layout()
plt.show()

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[95], line 28
     23             ax.text(k, j, format(c_matrix[j, k], 'd'),
     24                     ha="center", va="center",
     25                     color="white" if c_matrix[j, k] > c_matrix.max() / 2. else "black")
     26             break
---> 28 plt.tight_layout()
     29 plt.show()

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/pyplot.py:2584, in tight_layout(pad, h_pad, w_pad, rect)
   2576 @_copy_docstring_and_deprecators(Figure.tight_layout)
   2577 def tight_layout(
   2578     *,
   (...)
   2582     rect: tuple[float, float, float, float] | None = None,
   2583 ) -> None:
-> 2584     gcf().tight_layout(pad=pad, h_pad=h_pad, w_pad=w_pad, rect=rect)

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/figure.py:3540, in Figure.tight_layout(self, pad, h_pad, w_pad, rect)
   3538 previous_engine = self.get_layout_engine()
   3539 self.set_layout_engine(engine)
-> 3540 engine.execute(self)
   3541 if previous_engine is not None and not isinstance(
   3542     previous_engine, (TightLayoutEngine, PlaceHolderLayoutEngine)
   3543 ):
   3544     _api.warn_external('The figure layout has changed to tight')

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/layout_engine.py:181, in TightLayoutEngine.execute(self, fig)
    164 """
    165 Execute tight_layout.
    166 
   (...)
    178 .pyplot.tight_layout
    179 """
    180 info = self._params
--> 181 renderer = fig._get_renderer()
    182 with getattr(renderer, "_draw_disabled", nullcontext)():
    183     kwargs = get_tight_layout_figure(
    184         fig, fig.axes, get_subplotspec_list(fig.axes), renderer,
    185         pad=info['pad'], h_pad=info['h_pad'], w_pad=info['w_pad'],
    186         rect=info['rect'])

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/figure.py:2754, in Figure._get_renderer(self)
   2752 def _get_renderer(self):
   2753     if hasattr(self.canvas, 'get_renderer'):
-> 2754         return self.canvas.get_renderer()
   2755     else:
   2756         return _get_renderer(self)

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/backends/backend_agg.py:398, in FigureCanvasAgg.get_renderer(self)
    396 reuse_renderer = (self._lastKey == key)
    397 if not reuse_renderer:
--> 398     self.renderer = RendererAgg(w, h, self.figure.dpi)
    399     self._lastKey = key
    400 return self.renderer

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/backends/backend_agg.py:70, in RendererAgg.__init__(self, width, height, dpi)
     68 self.width = width
     69 self.height = height
---> 70 self._renderer = _RendererAgg(int(width), int(height), dpi)
     71 self._filter_renderers = []
     73 self._update_methods()

ValueError: Image size of 160000x400 pixels is too large. It must be less than 2^16 in each direction.

Error in callback <function _draw_all_if_interactive> (for post_execute), with arguments args (),kwargs {}:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/pyplot.py:197, in _draw_all_if_interactive()
    195 def _draw_all_if_interactive() -> None:
    196     if matplotlib.is_interactive():
--> 197         draw_all()

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/_pylab_helpers.py:132, in Gcf.draw_all(cls, force)
    130 for manager in cls.get_all_fig_managers():
    131     if force or manager.canvas.figure.stale:
--> 132         manager.canvas.draw_idle()

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/backend_bases.py:1893, in FigureCanvasBase.draw_idle(self, *args, **kwargs)
   1891 if not self._is_idle_drawing:
   1892     with self._idle_draw_cntx():
-> 1893         self.draw(*args, **kwargs)

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/backends/backend_agg.py:383, in FigureCanvasAgg.draw(self)
    381 def draw(self):
    382     # docstring inherited
--> 383     self.renderer = self.get_renderer()
    384     self.renderer.clear()
    385     # Acquire a lock on the shared font cache.

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/backends/backend_agg.py:398, in FigureCanvasAgg.get_renderer(self)
    396 reuse_renderer = (self._lastKey == key)
    397 if not reuse_renderer:
--> 398     self.renderer = RendererAgg(w, h, self.figure.dpi)
    399     self._lastKey = key
    400 return self.renderer

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/backends/backend_agg.py:70, in RendererAgg.__init__(self, width, height, dpi)
     68 self.width = width
     69 self.height = height
---> 70 self._renderer = _RendererAgg(int(width), int(height), dpi)
     71 self._filter_renderers = []
     73 self._update_methods()

ValueError: Image size of 160000x400 pixels is too large. It must be less than 2^16 in each direction.

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/IPython/core/formatters.py:340, in BaseFormatter.__call__(self, obj)
    338     pass
    339 else:
--> 340     return printer(obj)
    341 # Finally look for special method names
    342 method = get_real_method(obj, self.print_method)

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/IPython/core/pylabtools.py:152, in print_figure(fig, fmt, bbox_inches, base64, **kwargs)
    149     from matplotlib.backend_bases import FigureCanvasBase
    150     FigureCanvasBase(fig)
--> 152 fig.canvas.print_figure(bytes_io, **kw)
    153 data = bytes_io.getvalue()
    154 if fmt == 'svg':

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/backend_bases.py:2156, in FigureCanvasBase.print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs)
   2151 layout_engine = self.figure.get_layout_engine()
   2152 if layout_engine is not None or bbox_inches == "tight":
   2153     # we need to trigger a draw before printing to make sure
   2154     # CL works.  "tight" also needs a draw to get the right
   2155     # locations:
-> 2156     renderer = _get_renderer(
   2157         self.figure,
   2158         functools.partial(
   2159             print_method, orientation=orientation)
   2160     )
   2161     # we do this instead of `self.figure.draw_without_rendering`
   2162     # so that we can inject the orientation
   2163     with getattr(renderer, "_draw_disabled", nullcontext)():

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/backend_bases.py:1642, in _get_renderer(figure, print_method)
   1639     print_method = stack.enter_context(
   1640         figure.canvas._switch_canvas_and_return_print_method(fmt))
   1641 try:
-> 1642     print_method(io.BytesIO())
   1643 except Done as exc:
   1644     renderer, = exc.args

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/backend_bases.py:2043, in FigureCanvasBase._switch_canvas_and_return_print_method.<locals>.<lambda>(*args, **kwargs)
   2039     optional_kws = {  # Passed by print_figure for other renderers.
   2040         "dpi", "facecolor", "edgecolor", "orientation",
   2041         "bbox_inches_restore"}
   2042     skip = optional_kws - {*inspect.signature(meth).parameters}
-> 2043     print_method = functools.wraps(meth)(lambda *args, **kwargs: meth(
   2044         *args, **{k: v for k, v in kwargs.items() if k not in skip}))
   2045 else:  # Let third-parties do as they see fit.
   2046     print_method = meth

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/backends/backend_agg.py:497, in FigureCanvasAgg.print_png(self, filename_or_obj, metadata, pil_kwargs)
    450 def print_png(self, filename_or_obj, *, metadata=None, pil_kwargs=None):
    451     """
    452     Write the figure to a PNG file.
    453 
   (...)
    495         *metadata*, including the default 'Software' key.
    496     """
--> 497     self._print_pil(filename_or_obj, "png", pil_kwargs, metadata)

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/backends/backend_agg.py:445, in FigureCanvasAgg._print_pil(self, filename_or_obj, fmt, pil_kwargs, metadata)
    440 def _print_pil(self, filename_or_obj, fmt, pil_kwargs, metadata=None):
    441     """
    442     Draw the canvas, then save it using `.image.imsave` (to which
    443     *pil_kwargs* and *metadata* are forwarded).
    444     """
--> 445     FigureCanvasAgg.draw(self)
    446     mpl.image.imsave(
    447         filename_or_obj, self.buffer_rgba(), format=fmt, origin="upper",
    448         dpi=self.figure.dpi, metadata=metadata, pil_kwargs=pil_kwargs)

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/backends/backend_agg.py:383, in FigureCanvasAgg.draw(self)
    381 def draw(self):
    382     # docstring inherited
--> 383     self.renderer = self.get_renderer()
    384     self.renderer.clear()
    385     # Acquire a lock on the shared font cache.

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/backends/backend_agg.py:398, in FigureCanvasAgg.get_renderer(self)
    396 reuse_renderer = (self._lastKey == key)
    397 if not reuse_renderer:
--> 398     self.renderer = RendererAgg(w, h, self.figure.dpi)
    399     self._lastKey = key
    400 return self.renderer

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/matplotlib/backends/backend_agg.py:70, in RendererAgg.__init__(self, width, height, dpi)
     68 self.width = width
     69 self.height = height
---> 70 self._renderer = _RendererAgg(int(width), int(height), dpi)
     71 self._filter_renderers = []
     73 self._update_methods()

ValueError: Image size of 160000x400 pixels is too large. It must be less than 2^16 in each direction.

<Figure size 160000x400 with 320 Axes>

sns.heatmap(cm, annot=False)

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[94], line 1
----> 1 sns.heatmap(cm, annot=False)

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/seaborn/matrix.py:446, in heatmap(data, vmin, vmax, cmap, center, robust, annot, fmt, annot_kws, linewidths, linecolor, cbar, cbar_kws, cbar_ax, square, xticklabels, yticklabels, mask, ax, **kwargs)
    365 """Plot rectangular data as a color-encoded matrix.
    366 
    367 This is an Axes-level function and will draw the heatmap into the
   (...)
    443 
    444 """
    445 # Initialize the plotter object
--> 446 plotter = _HeatMapper(data, vmin, vmax, cmap, center, robust, annot, fmt,
    447                       annot_kws, cbar, cbar_kws, xticklabels,
    448                       yticklabels, mask)
    450 # Add the pcolormesh kwargs here
    451 kwargs["linewidths"] = linewidths

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/seaborn/matrix.py:110, in _HeatMapper.__init__(self, data, vmin, vmax, cmap, center, robust, annot, fmt, annot_kws, cbar, cbar_kws, xticklabels, yticklabels, mask)
    108 else:
    109     plot_data = np.asarray(data)
--> 110     data = pd.DataFrame(plot_data)
    112 # Validate the mask and convert to DataFrame
    113 mask = _matrix_mask(data, mask)

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/pandas/core/frame.py:827, in DataFrame.__init__(self, data, index, columns, dtype, copy)
    816         mgr = dict_to_mgr(
    817             # error: Item "ndarray" of "Union[ndarray, Series, Index]" has no
    818             # attribute "name"
   (...)
    824             copy=_copy,
    825         )
    826     else:
--> 827         mgr = ndarray_to_mgr(
    828             data,
    829             index,
    830             columns,
    831             dtype=dtype,
    832             copy=copy,
    833             typ=manager,
    834         )
    836 # For data is list-like, or Iterable (will consume into list)
    837 elif is_list_like(data):

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/pandas/core/internals/construction.py:314, in ndarray_to_mgr(values, index, columns, dtype, copy, typ)
    308     _copy = (
    309         copy_on_sanitize
    310         if (dtype is None or astype_is_view(values.dtype, dtype))
    311         else False
    312     )
    313     values = np.array(values, copy=_copy)
--> 314     values = _ensure_2d(values)
    316 else:
    317     # by definition an array here
    318     # the dtypes will be coerced to a single dtype
    319     values = _prep_ndarraylike(values, copy=copy_on_sanitize)

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/pandas/core/internals/construction.py:592, in _ensure_2d(values)
    590     values = values.reshape((values.shape[0], 1))
    591 elif values.ndim != 2:
--> 592     raise ValueError(f"Must pass 2-d input. shape={values.shape}")
    593 return values

ValueError: Must pass 2-d input. shape=(320, 2, 2)

# Create a heatmap
plt.figure(figsize=(8+4, 6+4))
sns.heatmap(cm, annot=False, fmt='d', cmap='Blues', xticklabels=label_encoder.classes_, yticklabels=label_encoder.classes_)
plt.xlabel("Predicted Label")
plt.ylabel("True Label")
plt.title("Confusion Matrix")

	0	1	2	3	4	5	6	7	8	9	...	317	318	319	320	321	322	323	324	325	326
0	0	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
1	0	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
2	0	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
3	0	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
4	0	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
5827	0	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
5828	0	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
5829	0	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
5830	0	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
5831	0	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0

5832 rows × 327 columns

from sklearn.preprocessing import MultiLabelBinarizer

mlb = MultiLabelBinarizer()
y = mlb.fit_transform(train['kinase_gene'])

# Save the list of kinase classes
kinase_classes = mlb.classes_

len(kinase_classes)

452

K-mer

import umap
from collections import Counter
from sklearn.preprocessing import StandardScaler

def extract_kmers(peptides, k):
    """Generate k-mer frequency feature vectors from a list of peptide sequences."""
    all_kmers = []
    feature_vectors = []

    # Collect all k-mers to create a global vocabulary
    for peptide in peptides:
        kmers = [peptide[i:i+k] for i in range(len(peptide) - k + 1)]
        all_kmers.extend(kmers)

    unique_kmers = list(set(all_kmers))  # Unique k-mers as features
    kmer_dict = {kmer: i for i, kmer in enumerate(unique_kmers)}

    # Generate feature vectors
    for peptide in peptides:
        kmers = [peptide[i:i+k] for i in range(len(peptide) - k + 1)]
        kmer_counts = Counter(kmers)
        vector = np.zeros(len(unique_kmers))

        for kmer, count in kmer_counts.items():
            vector[kmer_dict[kmer]] = count

        feature_vectors.append(vector)

    return np.array(feature_vectors), unique_kmers

peptides = df[SEQ_COL].tolist()

k = 1
feature_matrix, kmer_labels = extract_kmers(peptides, k)

# Normalize features
scaler = StandardScaler()
feature_matrix_scaled = scaler.fit_transform(feature_matrix)

feature_matrix_scaled.columns=['kmer1_'+i for i in kmer_labels]

feature_matrix_scaled.head()

	kmer1__	kmer1_W	kmer1_I	kmer1_H	kmer1_S	kmer1_L	kmer1_Q	kmer1_V	kmer1_t	kmer1_E	...	kmer1_R	kmer1_A	kmer1_M	kmer1_F	kmer1_y	kmer1_Y	kmer1_C	kmer1_P	kmer1_N	kmer1_T
0	-0.292368	-0.534618	-0.381885	0.185877	0.705791	1.538938	-1.153188	-1.372517	-0.827500	3.041615	...	-0.323779	1.174198	-0.811313	-1.005910	-0.722063	-0.628547	1.630311	-1.163877	-0.330899	-0.183614
1	-0.292368	-0.534618	0.350920	2.264674	-0.385998	0.475219	0.139184	-0.067668	1.667494	0.357542	...	-1.372446	-0.881089	-0.811313	0.732836	0.332195	-0.628547	1.630311	-0.291796	0.437719	0.611965
2	-0.292368	-0.534618	0.350920	2.264674	-0.931893	0.475219	-0.507002	-0.067668	1.667494	0.357542	...	-1.372446	-0.881089	-0.811313	0.732836	0.332195	0.515607	1.630311	0.144245	0.437719	0.611965
3	-0.292368	-0.534618	-0.381885	0.185877	-0.931893	-0.588501	-1.153188	1.237181	-0.827500	0.804887	...	-0.848113	0.660376	-0.811313	0.732836	-0.722063	-0.628547	-0.608818	1.016327	0.437719	0.611965
4	-0.292368	-0.534618	-0.381885	0.185877	-0.931893	-0.588501	-1.153188	1.237181	-0.827500	0.804887	...	-1.372446	1.174198	-0.811313	2.471583	-0.722063	0.515607	-0.608818	0.580286	-0.330899	0.611965

5 rows × 24 columns

One-hot encode

	x0_A	x0_C	x0_D	x0_E	x0_F	x0_G	x0_H	x0_I	x0_K	x0_L	...	x40_R	x40_S	x40_T	x40_V	x40_W	x40_Y	x40__	x40_s	x40_t	x40_y
0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
1	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
2	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
3	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
4	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
29151	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
29152	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
29153	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
29154	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
29155	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0

29156 rows × 962 columns

# features= pd.concat([onehot,feature_matrix_scaled],axis=1)

Need to modify non-canonical

from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelEncoder
import xgboost as xgb
from sklearn.metrics import classification_report, confusion_matrix

label_encoder = LabelEncoder()

labels =np.array(df['kinase_pspa_small'].fillna('Others'))
y = label_encoder.fit_transform(labels)

onehot_encode(df['site_seq'])

	x0_A	x0_C	x0_D	x0_E	x0_F	x0_G	x0_H	x0_I	x0_K	x0_L	...	x40_R	x40_S	x40_T	x40_V	x40_W	x40_Y	x40__	x40_s	x40_t	x40_y
0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0
1	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
2	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
3	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0
4	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
29151	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0
29152	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
29153	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
29154	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
29155	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0

29156 rows × 962 columns

X = onehot_encode(train[SEQ_COL])

colname = X.columns.str[1:].tolist()
colname = [f"{int(item.split('_', 1)[0]) - 20}{item.split('_', 1)[1]}" for item in colname]

X.columns = colname
X.head()

	-20A	-20C	-20D	-20E	-20F	-20G	-20H	-20I	-20K	-20L	...	20R	20S	20T	20V	20W	20Y	20_	20s	20t	20y
0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0
1	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
2	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
3	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0
4	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0

5 rows × 962 columns

from sklearn.model_selection import train_test_split
from sklearn.multiclass import OneVsRestClassifier
from xgboost import XGBClassifier
from sklearn.metrics import classification_report, confusion_matrix
import matplotlib.pyplot as plt
import seaborn as sns

def get_train_result_multilabel(X, y, label_names):
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
    
    model = OneVsRestClassifier(
        XGBClassifier(
            objective='binary:logistic',
            eval_metric='logloss',
            # use_label_encoder=False,
            tree_method='hist'
        )
    )
    
    print("Training multi-label model...")
    model.fit(X_train, y_train)
    
    print("Predicting...")
    y_pred = model.predict(X_test)

    print("Classification Report:")
    print(classification_report(y_test, y_pred, target_names=label_names, zero_division=0))
    
    return model, (X_train, X_test, y_train, y_test, y_pred)

model, data_split = get_train_result_multilabel(X, y, label_names=mlb.classes_)

Training multi-label model...

/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:32] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:33] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:34] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:36] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:37] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:39] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:40] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:42] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:43] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:44] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:45] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:47] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:48] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:49] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:51] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:52] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:53] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:54] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:56] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:57] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:09:58] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:00] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:01] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:02] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:04] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:05] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:06] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:08] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:09] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:10] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:11] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:13] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:14] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:16] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:17] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:18] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:19] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:21] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:22] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:23] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:25] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:26] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:28] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:29] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:30] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:32] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:34] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:35] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:37] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:38] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:39] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:40] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/sklearn/multiclass.py:90: UserWarning: Label not 52 is present in all training examples.
  warnings.warn(
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:42] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:43] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:45] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:46] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:47] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:48] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:50] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:51] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:52] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:54] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:55] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:56] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:58] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/sklearn/multiclass.py:90: UserWarning: Label not 66 is present in all training examples.
  warnings.warn(
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:10:59] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:00] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:02] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:03] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:04] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:06] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:07] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/sklearn/multiclass.py:90: UserWarning: Label not 74 is present in all training examples.
  warnings.warn(
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:08] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:10] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:11] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:13] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:14] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:15] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:17] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:18] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:20] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:21] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:22] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:24] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:25] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:26] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:28] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:29] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:30] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:32] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:33] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:34] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:36] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:37] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:38] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:40] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:41] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:42] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:44] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:45] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:47] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:48] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:49] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:51] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:52] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:54] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:55] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:57] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:11:58] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:00] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:01] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:02] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:04] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:05] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:07] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:08] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:09] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:11] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:12] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:14] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:15] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:16] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:18] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:19] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:21] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:22] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:24] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:25] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:26] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/sklearn/multiclass.py:90: UserWarning: Label not 132 is present in all training examples.
  warnings.warn(
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:28] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:29] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:30] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:32] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:33] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:34] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:36] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:37] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:39] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:41] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:42] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:43] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:45] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:46] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:48] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:49] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:50] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:52] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:53] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:55] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:56] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:58] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:12:59] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:00] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:02] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:04] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:05] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:07] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:08] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:09] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:10] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:12] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:13] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:15] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:16] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:17] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:19] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:20] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:22] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:23] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:25] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:26] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:28] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:29] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:30] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:32] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:33] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:34] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:36] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:37] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:38] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:40] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:41] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:42] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:44] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:45] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:47] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:48] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:49] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:51] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:52] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:53] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:55] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:56] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:57] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:13:59] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:00] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:02] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:04] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:05] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:07] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:08] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:09] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:10] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:12] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:13] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:15] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:16] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:18] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:19] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:20] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:22] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:23] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:24] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:26] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:27] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:29] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:30] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:31] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:33] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:34] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:36] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:37] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:38] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:40] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:41] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:43] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:44] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:46] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:47] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:48] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:50] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:51] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:53] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:54] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:55] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:57] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:58] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:14:59] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:00] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:02] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:03] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:05] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:06] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:07] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:09] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:10] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:11] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:13] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:14] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:16] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:17] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:19] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:20] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:21] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:22] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/sklearn/multiclass.py:90: UserWarning: Label not 259 is present in all training examples.
  warnings.warn(
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:24] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:25] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:27] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:28] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/sklearn/multiclass.py:90: UserWarning: Label not 264 is present in all training examples.
  warnings.warn(
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:29] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:31] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:32] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:33] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:34] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:36] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:37] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/sklearn/multiclass.py:90: UserWarning: Label not 272 is present in all training examples.
  warnings.warn(
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:38] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:40] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:41] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:43] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:44] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:45] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../xgboost/training.py:183: UserWarning: [14:15:47] WARNING: /workspace/src/learner.cc:738: 
Parameters: { "use_label_encoder" } are not used.

  bst.update(dtrain, iteration=i, fobj=obj)

def get_train_result(X,y):
    X=X.copy()
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2,stratify=y, random_state=42)
    num_classes=len(set(y))
    # Convert to XGBoost DMatrix format
    dtrain = xgb.DMatrix(X_train, label=y_train)
    dtest = xgb.DMatrix(X_test, label=y_test)
    
    # Set XGBoost parameters
    params = {
        'objective': 'multi:softmax',  # Multi-class classification
        'num_class': num_classes,
        'eval_metric': 'mlogloss',
        'max_depth': 6,
        'eta': 0.1,
        'tree_method': 'hist'
    }
        
    
    # Train model
    print('training')
    model = xgb.train(params, dtrain, num_boost_round=100)

    print('predict on test')
    # Evaluate accuracy
    y_pred = model.predict(dtest)
    y_pred = np.round(y_pred).astype(int)
    # accuracy = (y_pred == y_test).mean()

    
    fig, ax = plt.subplots(figsize=(10, 6))  # Adjust figure size
    xgb.plot_importance(model, importance_type="weight", max_num_features=30, ax=ax)
    plt.title(f"Top {30} Most Important Features")
    plt.show()

    # Get detailed metrics
    report = classification_report(y_test, 
                                   y_pred, 
                                   target_names = label_encoder.classes_,
                                   digits=4, zero_division=0)
    print(report)
    
    
    # Compute confusion matrix
    cm = confusion_matrix(y_test, y_pred)
    
    # Create a heatmap
    plt.figure(figsize=(8+4, 6+4))
    sns.heatmap(cm, annot=False, fmt='d', cmap='Blues', xticklabels=label_encoder.classes_, yticklabels=label_encoder.classes_)
    plt.xlabel("Predicted Label")
    plt.ylabel("True Label")
    plt.title("Confusion Matrix")
    
    # plt.savefig('CM.png')
    plt.show()
    return model, (X_train, X_test, y_train, y_test,y_pred)

# X=onehot.copy()

model, data = get_train_result(X,y)

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[120], line 1
----> 1 model, data = get_train_result(X,y)

Cell In[118], line 3, in get_train_result(X, y)
      1 def get_train_result(X,y):
      2     X=X.copy()
----> 3     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2,stratify=y, random_state=42)
      4     num_classes=len(set(y))
      5     # Convert to XGBoost DMatrix format

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/sklearn/utils/_param_validation.py:216, in validate_params.<locals>.decorator.<locals>.wrapper(*args, **kwargs)
    210 try:
    211     with config_context(
    212         skip_parameter_validation=(
    213             prefer_skip_nested_validation or global_skip_validation
    214         )
    215     ):
--> 216         return func(*args, **kwargs)
    217 except InvalidParameterError as e:
    218     # When the function is just a wrapper around an estimator, we allow
    219     # the function to delegate validation to the estimator, but we replace
    220     # the name of the estimator by the name of the function in the error
    221     # message to avoid confusion.
    222     msg = re.sub(
    223         r"parameter of \w+ must be",
    224         f"parameter of {func.__qualname__} must be",
    225         str(e),
    226     )

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/sklearn/model_selection/_split.py:2872, in train_test_split(test_size, train_size, random_state, shuffle, stratify, *arrays)
   2868         CVClass = ShuffleSplit
   2870     cv = CVClass(test_size=n_test, train_size=n_train, random_state=random_state)
-> 2872     train, test = next(cv.split(X=arrays[0], y=stratify))
   2874 train, test = ensure_common_namespace_device(arrays[0], train, test)
   2876 return list(
   2877     chain.from_iterable(
   2878         (_safe_indexing(a, train), _safe_indexing(a, test)) for a in arrays
   2879     )
   2880 )

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/sklearn/model_selection/_split.py:1909, in BaseShuffleSplit.split(self, X, y, groups)
   1879 """Generate indices to split data into training and test set.
   1880 
   1881 Parameters
   (...)
   1906 to an integer.
   1907 """
   1908 X, y, groups = indexable(X, y, groups)
-> 1909 for train, test in self._iter_indices(X, y, groups):
   1910     yield train, test

File /home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/sklearn/model_selection/_split.py:2318, in StratifiedShuffleSplit._iter_indices(self, X, y, groups)
   2316 class_counts = np.bincount(y_indices)
   2317 if np.min(class_counts) < 2:
-> 2318     raise ValueError(
   2319         "The least populated class in y has only 1"
   2320         " member, which is too few. The minimum"
   2321         " number of groups for any class cannot"
   2322         " be less than 2."
   2323     )
   2325 if n_train < n_classes:
   2326     raise ValueError(
   2327         "The train_size = %d should be greater or "
   2328         "equal to the number of classes = %d" % (n_train, n_classes)
   2329     )

ValueError: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.

model, data = get_train_result(X,y)

training
predict on test

                                    precision    recall  f1-score   support

                               ABL     0.3103    0.1314    0.1846       137
                               ACK     0.6667    0.0833    0.1481        24
                          AKT/ROCK     0.3057    0.3105    0.3081       190
                         ALPHA/MLK     0.1493    0.0746    0.0995       134
                              AMPK     0.1818    0.0920    0.1221        87
                          AURK/PKA     0.3206    0.5437    0.4034       263
                             CAMK2     0.4000    0.0408    0.0741        49
                             CDK_I     0.5067    0.4824    0.4943       313
                            CDK_II     0.7778    0.1321    0.2258        53
                               CK1     0.2041    0.1923    0.1980       104
                               CK2     0.4405    0.5988    0.5076       167
                              CMGC     0.2500    0.0500    0.0833        40
                         DYRK/HIPK     0.1379    0.0611    0.0847       131
        Discoidin domain receptors     1.0000    0.2727    0.4286        11
                     EGF receptors     0.2667    0.0588    0.0964        68
                        EIF2AK/TLK     0.2262    0.1776    0.1990       107
                  Ephrin receptors     0.6667    0.1359    0.2258       103
                            FAM20C     0.0000    0.0000    0.0000         2
            FGF and VEGF receptors     0.4118    0.0593    0.1037       118
                               GRK     0.2143    0.0577    0.0909        52
                              GSK3     0.3333    0.2222    0.2667        72
                               IKK     0.2238    0.4612    0.3014       232
Insulin and neurotrophin receptors     0.3103    0.1374    0.1905       131
                               JAK     0.3750    0.0316    0.0583        95
                          LATS/NDR     0.2000    0.0484    0.0779        62
                         LKB/CAMKK     0.5714    0.1290    0.2105        31
     LKB/CAMKK_Non-canonical (WEE)     0.0000    0.0000    0.0000         4
                             MAP3K     0.2927    0.1091    0.1589       110
                             MAP4K     0.2433    0.5000    0.3273       236
                              MAPK     0.3871    0.6949    0.4972       390
                          MARK/SIK     0.1954    0.1809    0.1878        94
                         MLCK/DAPK     1.0000    0.0833    0.1538        24
                               NAK     0.0000    0.0000    0.0000         9
                           NEK/ASK     0.2105    0.0825    0.1185        97
              Non-canonical (PDHK)     0.0000    0.0000    0.0000         5
               Non-canonical (WEE)     0.0000    0.0000    0.0000        26
                            Others     0.0870    0.0253    0.0392        79
                             PAK_I     0.2667    0.0426    0.0734        94
                            PAK_II     0.0000    0.0000    0.0000        17
                    PDGF receptors     0.2818    0.5927    0.3820       329
                              PIKK     0.3495    0.7386    0.4745        88
                               PKC     0.2645    0.3133    0.2868       233
                               PLK     0.1579    0.0417    0.0659        72
                      PRKD/MAPKAPK     0.2090    0.2476    0.2267       206
                          RIPK/WNK     0.3333    0.0294    0.0541        68
                           S6K/RSK     0.1379    0.0580    0.0816       138
                               SRC     0.3143    0.5537    0.4010       298
                          SRPK/CLK     1.0000    0.0952    0.1739        21
                       SYK and FAK     0.0000    0.0000    0.0000        28
                     TAM receptors     0.3200    0.0684    0.1127       117
                               TEC     0.0000    0.0000    0.0000        52
                             TGFBR     0.2692    0.3294    0.2963        85
                          ULK/TTBK     0.5556    0.1587    0.2469        63
                          assorted     0.0000    0.0000    0.0000        60
     assorted_Non-canomical (PDHK)     0.0000    0.0000    0.0000         1
     assorted_Non-canonical (PDHK)     0.0000    0.0000    0.0000         4
                        basophilic     0.0000    0.0000    0.0000         8

                          accuracy                         0.3044      5832
                         macro avg     0.2864    0.1672    0.1674      5832
                      weighted avg     0.3034    0.3044    0.2607      5832

gain_scores = model.get_score(importance_type='gain')

gain_pssm = recover_pssm(pd.Series(gain_scores))

plot_logo_heatmap(gain_pssm,figsize=(14,10),include_zero=False)

weight_scores = model.get_score(importance_type='weight')

weight_pssm = recover_pssm(pd.Series(weight_scores))

plot_logo_heatmap(weight_pssm,figsize=(14,10),include_zero=False)

fig, ax = plt.subplots(figsize=(10, 6))  # Adjust figure size
xgb.plot_importance(model, importance_type="weight", max_num_features=30, ax=ax)
plt.title(f"Top {30} Most Important Features")
plt.show()

from sklearn.metrics import classification_report

# Get detailed metrics
report = classification_report(y_test, 
                               y_pred, 
                               target_names = label_encoder.classes_,
                               digits=4, zero_division=0)
print(report)

print(report)

                                    precision    recall  f1-score   support

                               ABL     0.2656    0.5770    0.3638       331
                               ACK     0.2273    0.1087    0.1471        46
                          AKT/ROCK     0.3539    0.3500    0.3520       180
                         ALPHA/MLK     0.1481    0.0984    0.1182       122
                              AMPK     0.2113    0.1442    0.1714       104
                          AURK/PKA     0.3537    0.6268    0.4522       351
                             CAMK2     0.1552    0.0789    0.1047       114
                             CDK_I     0.4790    0.5245    0.5007       326
                            CDK_II     1.0000    0.0192    0.0377        52
                               CK1     0.1905    0.2286    0.2078       140
                               CK2     0.3952    0.6117    0.4802       188
                              CMGC     0.1818    0.0417    0.0678        48
                         DYRK/HIPK     0.2266    0.1593    0.1871       182
        Discoidin domain receptors     0.4000    0.0667    0.1143        30
                     EGF receptors     0.5455    0.0896    0.1538        67
                        EIF2AK/TLK     0.2152    0.2615    0.2361       130
                  Ephrin receptors     0.2316    0.2066    0.2184       213
                            FAM20C     0.0000    0.0000    0.0000         2
            FGF and VEGF receptors     0.0000    0.0000    0.0000       115
                               GRK     0.0909    0.0213    0.0345        47
                              GSK3     0.2179    0.1753    0.1943        97
                               IKK     0.2172    0.4076    0.2834       211
Insulin and neurotrophin receptors     0.3750    0.0600    0.1034        50
                               JAK     1.0000    0.0370    0.0714        27
                          LATS/NDR     0.2857    0.0784    0.1231        51
                         LKB/CAMKK     0.2500    0.2308    0.2400        52
     LKB/CAMKK_Non-canonical (WEE)     0.0000    0.0000    0.0000         4
                             MAP3K     0.1250    0.0256    0.0426        78
                             MAP4K     0.2432    0.4876    0.3245       201
                              MAPK     0.3787    0.5850    0.4598       347
                          MARK/SIK     0.2000    0.0843    0.1186        83
                         MLCK/DAPK     0.3333    0.0357    0.0645        28
                               NAK     0.0000    0.0000    0.0000         8
                           NEK/ASK     0.1250    0.0532    0.0746        94
              Non-canonical (PDHK)     0.0000    0.0000    0.0000         4
               Non-canonical (WEE)     0.0000    0.0000    0.0000        16
                             PAK_I     0.0667    0.0128    0.0215        78
                            PAK_II     0.0000    0.0000    0.0000        17
                    PDGF receptors     0.2174    0.1707    0.1913       205
                              PIKK     0.3696    0.7473    0.4945        91
                               PKC     0.2932    0.3411    0.3153       214
                               PLK     0.1515    0.0575    0.0833        87
                      PRKD/MAPKAPK     0.2767    0.2431    0.2588       181
                          RIPK/WNK     0.2273    0.1031    0.1418        97
                           S6K/RSK     0.2766    0.1066    0.1538       122
                               SRC     0.2587    0.3436    0.2952       259
                          SRPK/CLK     0.6000    0.1304    0.2143        23
                       SYK and FAK     0.7500    0.0833    0.1500        36
                     TAM receptors     0.2000    0.0484    0.0779       124
                               TEC     0.2000    0.0300    0.0522       100
                             TGFBR     0.2324    0.3204    0.2694       103
                          ULK/TTBK     0.0000    0.0000    0.0000        49
                          assorted     0.0000    0.0000    0.0000        62
     assorted_Non-canomical (PDHK)     0.0000    0.0000    0.0000         2
     assorted_Non-canonical (PDHK)     0.0000    0.0000    0.0000         5
                        basophilic     0.0000    0.0000    0.0000        10
                            others     0.0000    0.0000    0.0000       125

                          accuracy                         0.2899      6129
                         macro avg     0.2376    0.1616    0.1538      6129
                      weighted avg     0.2681    0.2899    0.2494      6129

accuracy

0.2899331049110785

import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.metrics import confusion_matrix
import xgboost as xgb
from sklearn.metrics import confusion_matrix
import seaborn as sns

# Convert test data to DMatrix format
dtest = xgb.DMatrix(X_test)

# Predict class labels
y_pred = model.predict(dtest)

# Convert predictions to integers (if not already)
y_pred = np.round(y_pred).astype(int)




# Compute confusion matrix
cm = confusion_matrix(y_test, y_pred)




# Create a heatmap
plt.figure(figsize=(8+4, 6+4))
sns.heatmap(cm, annot=False, fmt='d', cmap='Blues', xticklabels=label_encoder.classes_, yticklabels=label_encoder.classes_)
plt.xlabel("Predicted Label")
plt.ylabel("True Label")
plt.title("Confusion Matrix")

plt.savefig('CM.png')
plt.show()

# pip install shap

import shap

explainer = shap.TreeExplainer(model)

shap_values = explainer(X_test)

shap.initjs()

# Create SHAP explainer

  1%|                   | 2817/349353 [04:08<508:27]       

shap.summary_plot(shap_values, X_test, feature_names=X.columns.tolist())

y_pred

array([ 7.,  0., 10., ..., 45., 10., 28.], dtype=float32)

accuracy

0.2935225974873552

pspa_small

kinase
AAK1              NAK
ABL1              ABL
ABL2              ABL
TNK2              ACK
ACVR2A          TGFBR
             ...     
YSK1            MAP4K
ZAK             MAP3K
ZAP70     SYK and FAK
EEF2K       ALPHA/MLK
FAM20C         FAM20C
Name: pspa_category_small, Length: 522, dtype: object

from fastcore.utils import L

onehot

	-7A	-7C	-7D	-7E	-7F	-7G	-7H	-7I	-7K	-7L	-7M	-7N	-7P	-7Q	-7R	-7S	-7T	-7V	-7W	-7Y	-7_	-7s	-7t	-7y	-6A	-6C	-6D	-6E	-6F	-6G	-6H	-6I	-6K	-6L	-6M	-6N	-6P	-6Q	-6R	-6S	-6T	-6V	-6W	-6Y	-6_	-6s	-6t	-6y	-5A	-5C	-5D	-5E	-5F	-5G	-5H	-5I	-5K	-5L	-5M	-5N	-5P	-5Q	-5R	-5S	-5T	-5V	-5W	-5Y	-5_	-5s	-5t	-5y	-4A	-4C	-4D	-4E	-4F	-4G	-4H	-4I	-4K	-4L	-4M	-4N	-4P	-4Q	-4R	-4S	-4T	-4V	-4W	-4Y	-4_	-4s	-4t	-4y	-3A	-3C	-3D	-3E	-3F	-3G	-3H	-3I	-3K	-3L	-3M	-3N	-3P	-3Q	-3R	-3S	-3T	-3V	-3W	-3Y	-3_	-3s	-3t	-3y	-2A	-2C	-2D	-2E	-2F	-2G	-2H	-2I	-2K	-2L	-2M	-2N	-2P	-2Q	-2R	-2S	-2T	-2V	-2W	-2Y	-2_	-2s	-2t	-2y	-1A	-1C	-1D	-1E	-1F	-1G	-1H	-1I	-1K	-1L	-1M	-1N	-1P	-1Q	-1R	-1S	-1T	-1V	-1W	-1Y	-1_	-1s	-1t	-1y	0s	0t	0y	1A	1C	1D	1E	1F	1G	1H	1I	1K	1L	1M	1N	1P	1Q	1R	1S	1T	1V	1W	1Y	1_	1s	1t	1y	2A	2C	2D	2E	2F	2G	2H	2I	2K	2L	2M	2N	2P	2Q	2R	2S	2T	2V	2W	2Y	2_	2s	2t	2y	3A	3C	3D	3E	3F	3G	3H	3I	3K	3L	3M	3N	3P	3Q	3R	3S	3T	3V	3W	3Y	3_	3s	3t	3y	4A	4C	4D	4E	4F	4G	4H	4I	4K	4L	4M	4N	4P	4Q	4R	4S	4T	4V	4W	4Y	4_	4s	4t	4y	5A	5C	5D	5E	5F	5G	5H	5I	5K	5L	5M	5N	5P	5Q	5R	5S	5T	5V	5W	5Y	5_	5s	5t	5y	6A	6C	6D	6E	6F	6G	6H	6I	6K	6L	6M	6N	6P	6Q	6R	6S	6T	6V	6W	6Y	6_	6s	6t	6y	7A	7C	7D	7E	7F	7G	7H	7I	7K	7L	7M	7N	7P	7Q	7R	7S	7T	7V	7W	7Y	7_	7s	7t	7y
0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
1	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
2	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0
3	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
4	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
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30644 rows × 339 columns

# import seaborn as sns

# group_colors = {
#     'AG': '#037f04',
#     'DEsty': '#da143e',
#     'F': '#84380b',
#     'HQN': '#8d2be1',
#     'LMIFWTVC': '#d9a41c',
#     'P': '#000000',
#     'RK': '#0000ff',
#     'ST': '#8d008d',
#     'Y': '#84380b',
#     '_': 'yellow'
# }

# aa_color_map = {}
# for group, base_color in group_colors.items():
#     # Create a light palette (from base_color to white) with as many colors as letters in the group
#     palette = sns.light_palette(base_color, n_colors=8, input="hex",reverse=True)
#     # Assign each letter in the group a progressively lighter color
#     for i, aa in enumerate(sorted(group)):
#         aa_color_map[aa] = palette[i]

# df = Data.get_ks_dataset()

tab20bc = sns.color_palette("tab20", 20) + [sns.color_palette("tab20b", 20)[::4][i] for i in [0,1,3,4]]

sns.color_palette("tab20c", 10)

sns.color_palette("tab20c", 25)

import seaborn as sns
def plot_2d(X: pd.DataFrame, # a dataframe that has first column to be x, and second column to be y
            **kwargs, # arguments for sns.scatterplot
            ):
    "Make 2D plot from a dataframe that has first column to be x, and second column to be y"
    plt.figure(figsize=(7,7))
    sns.scatterplot(data = X,x=X.columns[0],y=X.columns[1],alpha=0.7,**kwargs)

def plot_2d_style(embed,no_frame=False, **kwargs):
    plot_2d(embed,**kwargs)
    plt.legend(frameon=False,markerscale=8, bbox_to_anchor=(1, 1), loc='upper left')
    plt.tick_params(axis='both', which='both', length=0)
    if no_frame:
        ax = plt.gca()
        ax.set_frame_on(False)
        plt.xlabel('')
        plt.ylabel('')
    plt.xticks([])
    plt.yticks([])

pca_embed=reduce_feature(onehot,'pca',n=50,seed=None)
onhot_embed=reduce_feature(pca_embed,'umap',complexity=15,seed=None)

len(onehot)

29156

onhot_embed=reduce_feature(onehot,'umap',complexity=15,seed=None)

# pca_embed_onehot=reduce_feature(onehot,'pca',n=100,seed=None)
# pca_embed_kmer = reduce_feature(feature_matrix_scaled,'pca',n=5,seed=None)

# pca_embed=pd.concat([pca_embed_onehot,pca_embed_kmer],axis=1)

onhot_embed=reduce_feature(pca_embed_onehot,'umap',complexity=15,seed=None)

umap_model = umap.UMAP(metric='dice', random_state=42)

# Fit and transform the data
embedding = umap_model.fit_transform(onehot)

/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../umap/umap_.py:1887: UserWarning: gradient function is not yet implemented for dice distance metric; inverse_transform will be unavailable
  warn(
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../umap/umap_.py:1952: UserWarning: n_jobs value 1 overridden to 1 by setting random_state. Use no seed for parallelism.
  warn(

onhot_embed = pd.DataFrame(embedding)

pca_embed=reduce_feature(features,'pca',n=50,seed=None)

onhot_embed=reduce_feature(pca_embed,'umap',complexity=15,seed=None)

import prince

mca = prince.MCA(
    n_components=2,
    n_iter=3,
    copy=True,
    check_input=True,
    engine='sklearn',
    random_state=42,
    one_hot=False
)
mca = mca.fit_transform(onehot)

mca

	0	1
0	-0.099896	-0.122510
1	-0.109294	-0.122680
2	-0.091015	-0.120340
3	-0.097323	-0.133918
4	-0.110189	-0.111004
...	...	...
29151	-0.094846	-0.117303
29152	-0.094179	-0.077234
29153	-0.109504	-0.115057
29154	-0.101956	-0.130661
29155	-0.090492	-0.114562

29156 rows × 2 columns

import altair as alt
alt.data_transformers.enable("vegafusion")

DataTransformerRegistry.enable('vegafusion')

mca.eigenvalues_summary

	eigenvalue	% of variance	% of variance (cumulative)
component
0	0.334	1.49%	1.49%
1	0.292	1.30%	2.79%

center=len(df[SEQ_COL].iloc[0])//2

plot_2d_style(mca,s=1,hue=df[SEQ_COL].str[center])

plot_2d_style(onhot_embed,s=1,hue=df[SEQ_COL].str[center])

plot_2d_style(onhot_embed,s=1,hue=df[SEQ_COL].str[center])

plot_2d_style(onhot_embed,s=1,hue=df[SEQ_COL].str[center])

plot_2d_style(onhot_embed,s=1,hue=df[SEQ_COL].str[center])

hue_order=list('PGACSTVILMFYWHKRQNDEsty_')

plot_2d_style(onhot_embed,s=1,hue=df[SEQ_COL].str[center+1],palette=tab20bc,hue_order=hue_order)

group_hue = df.kinase_group.fillna('Other')

plot_2d_style(onhot_embed,s=1,hue=group_hue,palette=tab20bc)

/tmp/ipykernel_33835/2654063392.py:7: UserWarning: The palette list has more values (24) than needed (9), which may not be intended.
  sns.scatterplot(data = X,x=X.columns[0],y=X.columns[1],alpha=0.7,**kwargs)

group_hue = df.kinase_paper.map(group).fillna('Other')

hue_order=list('PGACSTVILMFYWHKRQNDEsty_')

plot_2d_style(onhot_embed,s=1,hue=df[SEQ_COL].str[8],palette=tab20bc,hue_order=hue_order)

plot_2d_style(onhot_embed,s=1,hue=group_hue,palette=tab20bc)

/tmp/ipykernel_7561/2523523824.py:7: UserWarning: The palette list has more values (24) than needed (9), which may not be intended.
  sns.scatterplot(data = X,x=X.columns[0],y=X.columns[1],alpha=0.7,**kwargs)

Qlabel=(df[SEQ_COL].str[8]=='Q').replace({True:'1Q',False:'others'})

plot_2d_style(onhot_embed,s=1,hue=Qlabel)

Not very much separation

Physicochemical encoded

aa = Data.get_aa_info().iloc[:-2,:]

feat = get_rdkit_df(aa,'SMILES')

removing columns: {'MaxEStateIndex', 'SlogP_VSA7', 'fr_N_O', 'fr_lactone', 'NumSaturatedHeterocycles', 'Chi2v', 'MaxPartialCharge', 'fr_dihydropyridine', 'SMR_VSA8', 'NumAmideBonds', 'fr_COO2', 'fr_pyridine', 'Chi0', 'fr_term_acetylene', 'fr_halogen', 'EState_VSA11', 'SlogP_VSA9', 'fr_isothiocyan', 'fr_nitrile', 'fr_Ar_COO', 'fr_alkyl_halide', 'fr_oxazole', 'fr_imidazole', 'fr_nitro', 'fr_prisulfonamd', 'ExactMolWt', 'NumRadicalElectrons', 'fr_Ndealkylation1', 'fr_priamide', 'SMR_VSA2', 'PEOE_VSA13', 'fr_Nhpyrrole', 'NumValenceElectrons', 'fr_benzene', 'fr_Ar_OH', 'fr_Imine', 'fr_Ar_NH', 'fr_para_hydroxylation', 'fr_allylic_oxid', 'fr_ester', 'VSA_EState1', 'fr_methoxy', 'Chi2n', 'fr_ketone', 'fr_aldehyde', 'fr_lactam', 'fr_benzodiazepine', 'fr_phos_acid', 'NumBridgeheadAtoms', 'SlogP_VSA12', 'fr_hdrzone', 'fr_urea', 'fr_ArN', 'NumAliphaticRings', 'BCUT2D_MRHI', 'fr_COO', 'fr_thiazole', 'fr_ether', 'fr_Al_OH_noTert', 'PEOE_VSA5', 'NumSaturatedRings', 'fr_Ndealkylation2', 'fr_amidine', 'SlogP_VSA6', 'fr_morpholine', 'fr_C_O_noCOO', 'fr_sulfone', 'fr_bicyclic', 'fr_nitro_arom', 'fr_azo', 'fr_hdrzine', 'fr_barbitur', 'LabuteASA', 'SlogP_VSA10', 'fr_C_S', 'VSA_EState9', 'fr_imide', 'Asphericity', 'MinAbsPartialCharge', 'fr_piperdine', 'fr_ketone_Topliss', 'fr_tetrazole', 'HeavyAtomMolWt', 'fr_oxime', 'fr_amide', 'PMI3', 'fr_azide', 'HeavyAtomCount', 'fr_sulfonamd', 'fr_aniline', 'fr_guanido', 'fr_alkyl_carbamate', 'fr_isocyan', 'fr_HOCCN', 'fr_diazo', 'fr_phos_ester', 'fr_nitroso', 'fr_thiocyan', 'fr_piperzine', 'Eccentricity', 'NumSaturatedCarbocycles', 'fr_furan', 'fr_phenol', 'NumSpiroAtoms', 'fr_thiophene', 'NumAliphaticCarbocycles', 'fr_epoxide', 'fr_quatN', 'fr_aryl_methyl', 'SlogP_VSA11', 'fr_phenol_noOrthoHbond', 'fr_nitro_arom_nonortho'}

plot_cluster(feat, name_list = aa.Name.tolist(), hue = 'aa', method = 'pca')

dist_df,sim_df = get_similarity(feat)

plot_matrix(dist_df,inverse_color=True)

plot_matrix(sim_df)

feat.shape

(23, 116)

def encode_seq(seq, encoder):
    vec = []
    feature_length = len(encoder.iloc[0])  # Get the length of feature vectors

    for aa in seq:
        if aa.upper() in encoder.index:
            vec.extend(encoder.loc[aa.upper()].tolist())
        else:
            vec.extend([0] * feature_length)  # Append zeros if AA is missing
    return vec

check_seq_df(df, SEQ_COL)

0        AEGLRPAsPLGLTQE
1        GGGAGPVsPQHHELT
2        LRGNVVPsPLPtRRt
3        GPMRRSKsPADSANG
4        PERsQEEsPPGSTKR
              ...       
30639    GGGEGNVsQVGRVWP
30640    SSYRALIsAFSRLTR
30641    MDRSKRNsIAGFPPR
30642    FKVRHRAsGQVMALK
30643    YEKDGDEsSPILTsF
Name: substrate, Length: 30644, dtype: object

encoded = df['substrate'].progress_apply(lambda x: encode_seq(x,feat))

encoded = encoded.apply(pd.Series)

get_train_result(encoded)

training
predict on test

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
Cell In[22], line 1
----> 1 get_train_result(encoded)

Cell In[13], line 31, in get_train_result(X)
     27 y_pred = np.round(y_pred).astype(int)
     28 # accuracy = (y_pred == y_test).mean()
---> 31 fig, ax = plt.subplots(figsize=(10, 6))  # Adjust figure size
     32 xgb.plot_importance(model, importance_type="weight", max_num_features=30, ax=ax)
     33 plt.title(f"Top {30} Most Important Features")

NameError: name 'plt' is not defined

encoded

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469	-0.308607	-0.308607	-0.291386	-0.458831	-0.213201	1.543487	-2.525343	-0.213201	-0.213201	-0.213201	-1.034337	-0.768981	-0.289564	-1.977723	-0.827478	0.597322	-0.512773	-1.420765	-0.649584	2.010995	0.251582	-0.617142	0.943337	-0.694539	0.242444	-0.316691	0.445994	-0.103504	-0.928071	-0.526259	-0.043918	0.556229	-0.562001	-0.523909	-1.453514	-1.038963	-0.702544	0.833573	-0.648508	-0.641610	-0.724841	-0.737085	-0.712697	-0.825083	-0.563530	-0.732682	-0.788433	-0.918720	0.570570	-0.418096	-0.521056	-0.836672	-1.023990	0.373629	-0.113045	-0.213201	-0.308607	-0.521596	-0.682582	-0.458413	-0.308393	-0.647398	-0.224260	-0.480351	1.021053	0.109427	-0.882977	-0.432331	-0.495561	0.634977	-0.695145	-0.511968	-0.308607	-0.482124	0.800756	-0.884527	-0.458430	-0.241607	-0.213201	-0.131058	0.586510	-0.66116	-0.922850	-0.621218	-0.611041	0.790873	-0.440926	-0.455591	-0.769976	0.487402	-0.285797	-0.733998	1.616607	-0.450977	-0.081738	-0.543976	-1.334746	0.505208	0.738526	0.040161	-0.222925	-0.213201	-0.458831	-0.308607	-0.493197	2.238608	0.331133	0.163663	-0.329293	-0.387298	-0.871719	-0.362143	-0.614352	-0.556890	-0.890879	-0.783861	-0.308607	3.240370	-0.291386	-0.458831	-0.213201	-0.428746	-0.291386	-0.213201	-0.213201	-0.213201	-0.445444	-0.776063	1.113066	-1.254281	-0.843553	-0.133065	0.327619	-0.289030	0.529107	-0.850496	0.398464	-2.686513	-0.525659	0.672620	0.229539	-0.309659	0.042430	0.516029	0.996183	-0.526883	-0.301723	-0.225347	-0.479661	-0.220456	-0.418278	0.289905	0.415667	0.169350	0.060175	0.910130	0.720925	0.781342	0.882740	0.434681	0.447828	0.215241	0.385311	0.154262	-1.004204	-0.151171	1.112881	1.885100	1.755861	2.075265	-0.113045	4.690416	-0.308607	-0.521596	1.273176	-0.458413	-0.308393	-0.647398	0.530671	0.699641	-0.694405	-0.688230	0.484986	1.633996	1.374052	0.606766	1.135685	-0.511968	-0.308607	3.304752	1.051682	-0.884527	2.003899	0.732822	-0.213201	1.546840	-0.535127	-0.661160	0.354870	3.061686	-0.611041	-0.435773	-0.440926	-0.455591	0.718611	1.803574	-0.285797	-0.675401	1.932760	1.901386	0.047833	-0.425325	0.406110	-0.150087	0.349099	2.811268	1.242013	-0.213201	-0.458831	-0.308607	-0.493197	-0.213201	0.331133	2.673169	0.932996	-0.387298	1.634474	-0.362143	1.848968	-0.556890	-1.039565	0.931759	-0.308607	-0.308607	-0.291386	-0.458831	-0.213201	3.515721	1.942572	-0.213201	-0.213201	-0.213201	0.365021	1.453200	-1.473082	0.448914	1.857432	-0.537387	-1.777282	-1.171321	0.529107	-0.850496	0.398464	-2.686513	-0.525659	0.672620	0.229539	-0.309659	0.042430	0.516029	0.996183	-0.526883	-0.301723	-0.225347	-0.479661	-0.220456	-0.418278	0.289905	0.415667	0.169350	0.060175	0.910130	0.720925	0.781342	0.882740	0.434681	0.447828	0.215241	0.385311	0.154262	-1.004204	-0.151171	1.112881	1.885100	1.755861	2.075265	-0.113045	4.690416	-0.308607	-0.521596	1.273176	-0.458413	-0.308393	-0.647398	0.530671	0.699641	-0.694405	-0.688230	0.484986	1.633996	1.374052	0.606766	1.135685	-0.511968	-0.308607	3.304752	1.051682	-0.884527	2.003899	0.732822	-0.213201	1.546840	-0.535127	-0.661160	0.354870	3.061686	-0.611041	-0.435773	-0.440926	-0.455591	0.718611	1.803574	-0.285797	-0.675401	1.932760	1.901386	0.047833	-0.425325	0.406110	-0.150087	0.349099	2.811268	1.242013	-0.213201	-0.458831	-0.308607	-0.493197	-0.213201	0.331133	2.673169	0.932996	-0.387298	1.634474	-0.362143	1.848968	-0.556890	-1.039565	0.931759	-0.308607	-0.308607	-0.291386	-0.458831	-0.213201	3.515721	1.942572	-0.213201	-0.213201	-0.213201	0.365021	1.453200	-1.473082	0.448914	1.857432	-0.537387	-1.777282	-1.171321	-0.649584	2.010995	0.251582	-0.617142	0.943337	-0.694539	0.242444	-0.316691	0.445994	-0.103504	-0.928071	-0.526259	-0.043918	0.556229	-0.562001	-0.523909	-1.453514	-1.038963	-0.702544	0.833573	-0.648508	-0.641610	-0.724841	-0.737085	-0.712697	-0.825083	-0.563530	-0.732682	-0.788433	-0.918720	0.570570	-0.418096	-0.521056	-0.836672	-1.023990	0.373629	-0.113045	-0.213201	-0.308607	-0.521596	-0.682582	-0.458413	-0.308393	-0.647398	-0.224260	-0.480351	1.021053	0.109427	-0.882977	-0.432331	-0.495561	0.634977	-0.695145	-0.511968	-0.308607	-0.482124	0.800756	-0.884527	-0.458430	-0.241607	-0.213201	-0.131058	0.586510	-0.661160	-0.922850	-0.621218	-0.611041	0.790873	-0.440926	-0.455591	-0.769976	0.487402	-0.285797	-0.733998	1.616607	-0.450977	-0.081738	-0.543976	-1.334746	0.505208	0.738526	0.040161	-0.222925	-0.213201	-0.458831	-0.308607	-0.493197	2.238608	0.331133	0.163663	-0.329293	-0.387298	-0.871719	-0.362143	-0.614352	-0.556890	-0.890879	-0.783861	-0.308607	3.240370	-0.291386	-0.458831	-0.213201	-0.428746	-0.291386	-0.213201	-0.213201	-0.213201	-0.445444	-0.776063	1.113066	-1.254281	-0.843553	-0.133065	0.327619	-0.289030
3	-2.659736	-0.303815	0.426781	-0.653267	-1.825779	-1.787914	0.192416	-0.289431	1.656688	0.268215	-0.661636	-0.527120	3.378062	-3.610682	3.529379	-2.476702	3.820823	2.339301	-1.599718	-0.777419	-1.078909	-1.994004	-1.984875	-1.719703	-1.901068	-1.763427	-1.790074	-1.882295	-1.312462	-1.397762	0.661861	-0.447122	-1.982221	-1.750939	0.162382	-1.088274	-2.991634	-0.213201	-0.308607	-0.521596	-0.682582	-0.458413	-0.308393	-0.647398	-1.107502	-0.480351	1.144933	-0.688230	-0.882977	-0.432331	-0.495561	-2.256429	1.135685	-0.511968	-0.308607	-0.482124	-1.275893	-0.884527	-0.458430	-1.381653	-0.213201	-0.945646	-1.645349	-0.66116	0.480336	-0.621218	-0.611041	-0.435773	-0.440926	-0.455591	0.835328	-1.876177	-0.285797	-0.833930	-0.821329	-0.600834	0.333776	-0.136249	-0.462400	-0.736399	-0.429755	-0.883541	-0.955395	-0.213201	-0.458831	-0.308607	-0.493197	-2.665009	-1.192079	-1.091089	-0.960437	-0.387298	-1.707117	-0.362143	-1.570724	-0.556890	-0.573846	-1.824997	-0.308607	-0.308607	-0.291386	-0.458831	-0.213201	-0.428746	-0.291386	-0.213201	-0.213201	-0.213201	-1.661486	-1.114165	0.490377	-1.650130	-1.730851	3.382363	0.372204	-0.634367	0.280001	-0.334373	0.630545	0.055833	3.962299	-0.793519	0.230539	-0.310204	0.445994	1.755094	1.292222	-0.526815	0.156428	1.016748	0.338924	0.290406	0.348255	0.096033	0.928961	-1.791428	-0.601193	-0.627759	-0.711936	-0.544819	-0.079577	-0.325168	0.513716	0.276996	0.961352	0.680851	0.661861	-0.365611	-1.422146	-1.341137	-1.740279	-1.207619	-0.113045	-0.213201	-0.308607	-0.521596	-0.682582	-0.458413	-0.308393	-0.647398	1.365567	-0.480351	-0.694405	-0.688230	-0.882977	1.633996	-2.365174	0.606766	1.135685	-0.511968	-0.308607	-0.624985	-0.104126	-0.884527	-0.458430	0.732822	-0.213201	-1.508973	-1.645349	-0.661160	0.372512	-0.621218	2.841313	-0.435773	-0.440926	-0.455591	0.718611	-1.876177	-0.285797	-0.687785	0.161397	-2.628012	0.817036	-0.230842	1.127001	0.139624	0.972182	-1.807243	-0.955395	4.690416	-0.458831	-0.308607	-0.493197	-0.213201	-1.192079	-1.091089	-0.960437	2.581989	-1.707117	-0.362143	-1.615163	1.272892	0.429755	-0.649469	-0.308607	-0.308607	-0.291386	-0.458831	-0.213201	1.543487	-2.525343	-0.213201	-0.213201	-0.213201	-1.034337	-0.768981	-0.289564	-1.977723	-0.827478	0.597322	-0.512773	-1.420765	0.056275	0.601482	0.471762	0.965126	-0.240342	0.052405	0.229605	-0.309695	1.118602	1.479746	1.390901	1.989774	0.268481	-0.303336	0.012599	0.028435	0.270933	0.381854	-0.076800	0.075729	-0.598016	-0.072121	0.348721	-0.256771	-0.208879	0.843670	-0.280751	0.706959	-0.377127	0.594028	1.460660	-0.378212	0.165098	1.162146	0.833353	-1.088274	-0.113045	-0.213201	-0.308607	-0.521596	-0.682582	-0.458413	3.112079	-0.647398	1.243491	-0.480351	-0.694405	-0.688230	1.816859	-0.432331	-0.495561	-0.366786	2.664147	-0.511968	-0.308607	-0.482124	0.955547	-0.884527	-0.458430	-0.324416	-0.213201	-0.945646	-0.535127	-0.66116	-0.922850	0.598568	0.413434	-0.435773	2.273766	0.236285	-0.769976	-0.626017	1.721376	-0.698907	-0.636995	-0.326842	2.026631	-0.376824	1.744600	-0.522169	0.972182	-0.883541	-0.955395	-0.213201	-0.458831	-0.308607	-0.493197	-0.213201	0.331133	-1.091089	-0.329293	-0.387298	0.799076	-0.362143	1.579684	-0.556890	0.845212	0.327629	-0.308607	-0.308607	-0.291386	-0.458831	-0.213201	-0.428746	-0.291386	-0.213201	4.690416	-0.213201	-0.165266	-0.039651	-0.552557	0.652353	0.187464	-0.152293	-0.420402	0.486664	0.529107	-0.850496	0.398464	-2.686513	-0.525659	0.672620	0.229539	-0.309659	0.042430	0.516029	0.996183	-0.526883	-0.301723	-0.225347	-0.479661	-0.220456	-0.418278	0.289905	0.415667	0.169350	0.060175	0.910130	0.720925	0.781342	0.882740	0.434681	0.447828	0.215241	0.385311	0.154262	-1.004204	-0.151171	1.112881	1.885100	1.755861	2.075265	-0.113045	4.690416	-0.308607	-0.521596	1.273176	-0.458413	-0.308393	-0.647398	0.530671	0.699641	-0.694405	-0.688230	0.484986	1.633996	1.374052	0.606766	1.135685	-0.511968	-0.308607	3.304752	1.051682	-0.884527	2.003899	0.732822	-0.213201	1.546840	-0.535127	-0.661160	0.354870	3.061686	-0.611041	-0.435773	-0.440926	-0.455591	0.718611	1.803574	-0.285797	-0.675401	1.932760	1.901386	0.047833	-0.425325	0.406110	-0.150087	0.349099	2.811268	1.242013	-0.213201	-0.458831	-0.308607	-0.493197	-0.213201	0.331133	2.673169	0.932996	-0.387298	1.634474	-0.362143	1.848968	-0.55689	-1.039565	0.931759	-0.308607	-0.308607	-0.291386	-0.458831	-0.213201	3.515721	1.942572	-0.213201	-0.213201	-0.213201	0.365021	1.453200	-1.473082	0.448914	1.857432	-0.537387	-1.777282	-1.171321	0.529107	-0.850496	0.398464	-2.686513	-0.525659	0.672620	0.229539	-0.309659	0.042430	0.516029	0.996183	-0.526883	-0.301723	-0.225347	-0.479661	-0.220456	-0.418278	0.289905	0.415667	0.169350	0.060175	0.910130	0.720925	0.781342	0.882740	0.434681	0.447828	0.215241	0.385311	0.154262	-1.004204	-0.151171	1.112881	1.885100	1.755861	...	0.040161	0.509544	-0.213201	-0.458831	-0.308607	-0.493197	-0.213201	0.331133	0.163663	0.301852	-0.387298	-0.036322	-0.362143	-0.377578	-0.556890	-0.772086	-0.727688	3.240370	-0.308607	-0.291386	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30644 rows × 1740 columns

embedding_df=reduce_feature(encoded,'umap')

/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/umap/umap_.py:1952: UserWarning: n_jobs value 1 overridden to 1 by setting random_state. Use no seed for parallelism.
  warn(

plot_2d_style(embedding_df,s=1,hue=df[SEQ_COL].str[7])

plot_2d_style(embedding_df,s=1,hue=group_hue,palette=tab20bc)

/tmp/ipykernel_7561/2523523824.py:7: UserWarning: The palette list has more values (24) than needed (9), which may not be intended.
  sns.scatterplot(data = X,x=X.columns[0],y=X.columns[1],alpha=0.7,**kwargs)

plot_2d_style(embedding_df,s=1,hue=df[SEQ_COL].str[8],palette=tab20bc,hue_order=hue_order)

plot_2d_style(embedding_df,s=1,hue=df[SEQ_COL].str[4],palette=tab20bc,hue_order=hue_order)

plot_2d_style(embedding_df,s=1,hue=Qlabel)

A little bit more seperation in terms of +1P group

Onehot + physicochemical

comb = pd.concat([onehot,encoded],axis=1)

comb_emb=reduce_feature(comb,'umap')

/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/logomaker/../umap/umap_.py:1952: UserWarning: n_jobs value 1 overridden to 1 by setting random_state. Use no seed for parallelism.
  warn(

plot_2d(comb_emb,s=1,hue=df[SEQ_COL].str[8]=="Q")

plot_2d(comb_emb,s=1,hue=df[SEQ_COL].str[8])

plot_2d(comb_emb,s=1,hue=df[SEQ_COL].str[7])

plot_2d(onehot_pos_emb,s=1,hue=df[SEQ_COL].str[8]=="Q")

No much difference with the physiochemical alone

PSPA motif encoded

Transformer based

Plot interactions: onehot + kinase features