Kaggle competition: Toxic Comment Classification Challenge
<SOS> metric: MCAUC Kaggle data source: toxic-comment-classification-challenge<import_modules>
from sklearn.preprocessing import QuantileTransformer<import_modules>
import pandas as pd
import os
import gc
import pickle
import datetime
import numpy as np
import pandas as pd
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import StratifiedKFold
from sklearn.metrics import log_loss
from sklearn.decomposition import PCA
from tqdm.notebook import tqdm
from time import time<import_modules>
import pandas as pd
import tensorflow as tf
import tensorflow.keras.backend as K
import tensorflow.keras.layers as L
import tensorflow.keras.models as M
from tensorflow.keras.callbacks import ReduceLROnPlateau, ModelCheckpoint
import tensorflow_addons as tfa
from sklearn.model_selection import KFold<load_from_csv>
glove = pd.read_csv(".. /input/nb-svm-strong-linear-baseline/submission.csv")
 subb = pd.read_csv('.. /input/fasttext-like-baseline-with-keras-lb-0-053/submission_bn_fasttext.csv')
 ave = pd.read_csv('.. /input/toxic-avenger/submission.csv')
 lstm = pd.read_csv('.. /input/toxicfiles/baselinelstm0069.csv')
 svm = pd.read_csv(".. /input/toxicfiles/lstmglove0072ge.csv" )
train_features = pd.read_csv('.. /input/lish-moa/train_features.csv')
 train_targets_scored = pd.read_csv('.. /input/lish-moa/train_targets_scored.csv')
 train_targets_nonscored = pd.read_csv('.. /input/lish-moa/train_targets_nonscored.csv')
 test_features = pd.read_csv('.. /input/lish-moa/test_features.csv')
 sample_submission = pd.read_csv('.. /input/lish-moa/sample_submission.csv' )<define_variables>
col = col.tolist()
col.remove('id' )
GENES = [col for col in train_features.columns if col.startswith('g-')]
CELLS = [col for col in train_features.columns if col.startswith('c-')]<normalization>
for i in col:
ble[i] =(2*subb[i] + 3*lstm[i] + 4*glove[i] + 5*svm[i] + ave[i])/ 15
<set_options><EOS> 
ble.to_csv('submission20.csv', index = False )