Skrypt.py

@@ -1,83 +0,0 @@
-#!/usr/bin/env python
-# coding: utf-8
-
-from sklearn.feature_extraction.text import TfidfVectorizer
-from sklearn.naive_bayes import MultinomialNB
-import string
-import csv
-from stop_words import get_stop_words
-
-stop_words = get_stop_words('polish')
-
-gnb = MultinomialNB()
-vectorizer = TfidfVectorizer()
-
-
-zdanie = []
-cyfra = []
-with open("train/train.tsv") as tsv:
-    for line in csv.reader(tsv, delimiter="\t"):
-        cyfra.append(line[0])
-        zdanie.append(line[1])
-        
-    prep0=[]
-    for x in zdanie:
-        temp = ""
-        for y in x.split():
-            y = y.strip().replace(",", "")
-            if y not in stop_words:
-                 temp = temp + " " + y
-        prep0.append(temp)
-
-    zdanie2 = vectorizer.fit_transform(prep0)
-    gnb.fit(zdanie2, cyfra)
-
-    
-    
-inp1 = open('dev-0/in.tsv', 'r', encoding="utf-8")
-out1 = open("dev-0/out.tsv", "w")
-
-linia1 = inp1.readlines()
-inp1.close()
-
-prep=[]
-for x in linia1:
-    temp = ""
-    for y in x.split():
-        y = y.strip().replace(",", "")
-        if y not in stop_words:
-             temp = temp + " " + y
-    prep.append(temp)
-    
-vectorizer1 = vectorizer.transform(prep)
-predict1 = gnb.predict(vectorizer1)
-print(predict1)
-
-for x in predict1:
-    out1.write(str(x) + '\n')
-out1.close()
-
-
-
-inp2 = open('test-A/in.tsv', 'r', encoding="utf-8")
-out2 = open("test-A/out.tsv", "w")
-
-linia2 = inp2.readlines()
-inp2.close()
-
-prep2=[]
-for x2 in linia2:
-    temp2 = ""
-    for y2 in x2.split():
-        y2 = y2.strip().replace(",", "")
-        if y2 not in stop_words:
-             temp2 = temp2 + " " + y2
-    prep2.append(temp2)
-    
-vectorizer2 = vectorizer.transform(prep2)
-predict2 = gnb.predict(vectorizer2)    
-print(predict2)
-
-for y in predict2:
-    out2.write(str(y) + '\n')
-out2.close()