dziala

main.py

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+from sklearn import preprocessing
+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.naive_bayes import MultinomialNB
+from sklearn.pipeline import make_pipeline
+
+import numpy as np
+
+eng = preprocessing.LabelEncoder()
+
+with open("train/in.tsv") as myFile:
+    tmp = myFile.readlines()
+    with open("train/expected.tsv") as finFile:
+        fin = finFile.readlines() 
+        fin = eng.fit_transform(fin)
+        with open("test-A/in.tsv") as tFile:
+            fic = tFile.readlines() 
+            gnb = make_pipeline(TfidfVectorizer(),MultinomialNB())
+            model = gnb.fit(tmp, fin)
+            fin_pred = model.predict(fic)
+            fin_pred = np.array(fin_pred)
+            np.set_printoptions(threshold = np.inf)
+            eFile = np.array2string(fin_pred.flatten(), precision = 2, separator = '\n',suppress_small = True)
+            myFile = open("test-A/out.tsv", "a")
+            myFile.write(eFile)