Main.py

@@ -1,19 +0,0 @@
-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)