update

program.py

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+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.linear_model import LinearRegression
+from stop_words import get_stop_words
+import pandas as pd
+
+
+
+vectorizer = TfidfVectorizer(stop_words=get_stop_words('polish'))
+reg = LinearRegression()
+colnames = ['start_date', 'end_date', 'title', 'sort_title', 'data']
+t = pd.read_csv('test-A/in.tsv', sep="\t", names=colnames)
+df = pd.read_csv('train/train.tsv', sep="\t", names=colnames)
+date = (df['start_date'] + df['end_date']) / 2
+train = vectorizer.fit_transform(df['data'])
+reg.fit(train, date)
+r = vectorizer.transform(t['data'])
+pred = reg.predict(r)
+with open('test-A/out.tsv', 'w') as file:
+    for e in pred:
+        file.write("%f\n" % e)