run.py

@@ -1,19 +0,0 @@
-from sklearn.feature_extraction.text import TfidfVectorizer
-from sklearn.naive_bayes import MultinomialNB
-from sklearn.pipeline import make_pipeline
-import sys
-import pandas as pd
-
-train_file = sys.argv[1]
-pred_x_file = sys.argv[2]
-
-train = pd.read_csv(train_file, sep='\t', header=None)
-pred_x = pd.read_csv(pred_x_file, sep='\t', header=None)
-train_x, train_y = train[1], train[0]
-
-model = make_pipeline(TfidfVectorizer(), MultinomialNB())
-
-model.fit(train_x, train_y)
-pred_y = model.predict(pred_x.stack())
-
-pd.DataFrame(pred_y).to_csv('out.tsv', header=False, index=None)