Kaggle competition: Toxic Comment Classification Challenge
%matplotlib inline
plt.rcParams['figure.figsize'] = [16, 10]<load_from_csv>
f_caps_gru = '.. /input/capsule-net-with-gru/submission.csv'
f_dual_embed_pl = '.. /input/submission-dual-embed-pl/submission_dual_embed(2 ).csv'
f_dual_embed_mish = '.. /input/bi-gru-lstm-dual-embedding-with-mish/submission.csv'
f_lstm_glove_tta = '.. /input/improved-lstm-baseline-glove-dropout-trainta/submission.csv'
f_dual_embed_dehyp = '.. /input/improved-lstm-baseline-bi-lstm-dual-embed-dehyp/submission.csv'
f_lstm_fast = '.. /input/improved-lstm-baseline-fasttext-dropout/submission.csv'
f_nbsvm = '.. /input/nb-svm-strong-linear-baseline/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'
train = pd.read_csv('.. /input/new-york-city-taxi-with-osrm/train.csv')
 test = pd.read_csv('.. /input/new-york-city-taxi-with-osrm/test.csv')
 pd.set_option('display.float_format', lambda x: '%.3f' % x)
 train.head()<filter>
p_caps_gru = pd.read_csv(f_caps_gru)
 p_dual_embed_pl = pd.read_csv(f_dual_embed_pl)
 p_dual_embed_mish = pd.read_csv(f_dual_embed_mish)
 p_lstm_glove_tta = pd.read_csv(f_lstm_glove_tta)
 p_dual_embed_dehyp = pd.read_csv(f_dual_embed_dehyp)
 p_lstm_fast = pd.read_csv(f_lstm_fast)
 p_nbsvm = pd.read_csv(f_nbsvm)
 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 )
m = np.mean(train['trip_duration'])
 s = np.std(train['trip_duration'])
 train = train[train['trip_duration'] <= m + 2*s]
train = train[train['trip_duration'] >= m - 2*s]
train.head()<filter>
label_cols = ['toxic', 'severe_toxic', 'obscene', 'threat', 'insult', 'identity_hate']
p_res = p_caps_gru.copy()
p_res[label_cols] =(p_caps_gru[label_cols] + p_dual_embed_pl[label_cols] + p_dual_embed_mish[label_cols] + p_lstm_glove_tta[label_cols] + p_dual_embed_dehyp[label_cols] + p_lstm_fast[label_cols] + p_nbsvm[label_cols] + p_bi_post[label_cols] + p_dpcnn[label_cols] + p_dmcnn[label_cols] + p_rcn[label_cols])/ 11
<data_type_conversions><EOS> 
p_res.to_csv('submission.csv', index=False )