import pandas as pd train['target'] = 0 test['target'] = 1 train_test = pd.concat([train, test], axis=0).reset_index(drop=True) train_test.head() import numpy as np import lightgbm as lgb from sklearn.model_selection import StratifiedKFold params = {'objective': 'binary', 'max_depth': 5, 'boosting': 'gbdt', 'metric': 'auc'} features = [col for col in train_test.columns if col not in ('target',)] o