26.6895

Main.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
+
+meh = TfidfVectorizer(stop_words = get_stop_words('polish'))
+linReg = LinearRegression()
+colnames = ['start_date', 'end_date', 'title', 'sort_title', 'data']
+t = pd.read_csv('test-A/in.tsv', sep = "\t", names = colnames)
+datFin = pd.read_csv('train/train.tsv', sep = "\t", names = colnames)
+date = (datFin['start_date'] + datFin['end_date']) / 2
+trn = meh.fit_transform(datFin['data'])
+linReg.fit(trn, date)
+r = meh.transform(t['data'])
+x = linReg.predict(r)
+with open('test-A/out.tsv', 'w') as file:
+    for each in x:
+        file.write("%f\n" % each)