simple linear regression 10% of train

run.py

@@ -0,0 +1,24 @@
+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.linear_model import LinearRegression
+import sys
+import pandas as pd
+
+train_file = sys.argv[1]
+pred_file = sys.argv[2]
+
+train = pd.read_csv(train_file, sep='\t', header=None)
+pred_x = pd.read_csv(pred_file, sep='\t', header=None)
+train_x, train_y = train[4], train[0]
+#pred_x = pred[4]
+pred_x = pred_x.stack()
+
+vectorizer = TfidfVectorizer()
+train_x = vectorizer.fit_transform(train_x)
+pred_x = vectorizer.transform(pred_x)
+
+model = LinearRegression()
+model.fit(train_x, train_y)
+
+pred_y = model.predict(pred_x)
+
+pd.DataFrame(pred_y).to_csv('out.tsv', header=False, index=None)