Kaggle competition: Toxic Comment Classification Challenge
print("End Train Test.................. " )<train_model>
f_caps_gru = '.. /input/capsule-net-with-gru/submission.csv'
f_dual_embed_mish = '.. /input/bi-gru-lstm-dual-embedding-with-mish/submission.csv'
f_bi_post = '.. /input/bi-post/10fold_lstmpp_am.csv'
f_dpcnn = '.. /input/dpcnn-wordcloud/10fold_dpcnn_test.csv'
f_dmcnn = '.. /input/dmcnn-demoji/10fold_dmcnn_am.csv'
f_rcn = '.. /input/rcn-capsule/10fold_capsule_am.csv'
f_attn_300d = '.. /input/attn-300d-am/10fold_attn_post_am.csv'
f_slgbm = '.. /input/simple-lightgbm-classifier/submission_001.csv'
f_cat_boost = '.. /input/cat-boost/results_preds_cat.csv'
print("Start Bureau................ " )<load_from_csv>
p_caps_gru = pd.read_csv(f_caps_gru)
 p_dual_embed_mish = pd.read_csv(f_dual_embed_mish)
 p_bi_post = pd.read_csv(f_bi_post)
 p_dpcnn = pd.read_csv(f_dpcnn)
 p_dmcnn = pd.read_csv(f_dmcnn)
 p_rcn = pd.read_csv(f_rcn)
 p_attn_300d = pd.read_csv(f_attn_300d)
 p_slgbm = pd.read_csv(f_slgbm)
 p_cat_boost = pd.read_csv(f_cat_boost )
bureau = pd.read_csv('.. /input/bureau.csv', nrows = num_rows )<load_from_csv>
label_cols = ['toxic', 'severe_toxic', 'obscene', 'threat', 'insult', 'identity_hate']
p_res = p_caps_gru.copy()
p_res[label_cols] =(p_cat_boost[label_cols] + p_slgbm[label_cols] + p_caps_gru[label_cols] + p_dual_embed_mish[label_cols] + p_bi_post[label_cols] + p_dpcnn[label_cols] + p_dmcnn[label_cols] + p_rcn[label_cols] + p_attn_300d[label_cols])/ 9
bb = pd.read_csv('.. /input/bureau_balance.csv', nrows = num_rows)
 bb, bb_cat = one_hot_encoder(bb, nan_as_category)
 bureau, bureau_cat = one_hot_encoder(bureau, nan_as_category )<merge>
p_res.to_csv('submission.csv', index=False )