added files

main.py

@@ -0,0 +1,26 @@
+from sklearn.naive_bayes import MultinomialNB
+from sklearn.preprocessing import LabelEncoder
+from sklearn.pipeline import Pipeline
+from sklearn.feature_extraction.text import TfidfVectorizer
+import numpy as np
+
+def getData(path):
+    with open(path) as source:
+          return source.readlines()
+
+trainInData = getData('./train/in.tsv')
+trainExpData = getData('./train/expected.tsv')
+afterTransform = LabelEncoder().fit_transform(trainExpData)
+pipeline = Pipeline(steps=[('tfidf', TfidfVectorizer()),('naive-bayes', MultinomialNB())])
+
+model = pipeline.fit(trainInData, afterTransform)
+
+def getResult(path):
+  dataToPredict = getData(path + 'in.tsv')
+  pred = model.predict(dataToPredict)
+  with open(path + "out.tsv", "w") as result:
+    for prediction in pred:
+      result.write(str(prediction) + '\n')
+
+getResult('./dev-0/')
+getResult('./test-A/')