update

program.py

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+import numpy as np
+from sklearn import preprocessing
+from sklearn.naive_bayes import MultinomialNB
+from sklearn.pipeline import make_pipeline
+from sklearn.feature_extraction.text import TfidfVectorizer
+
+le=preprocessing.LabelEncoder()
+
+
+with open("train/in.tsv") as f:
+    X = f.readlines()
+    with open("train/expected.tsv") as ff:
+        Y = ff.readlines() 
+        Y= le.fit_transform(Y)
+        with open("test-A/in.tsv") as d:
+            r = d.readlines() 
+            gnb = make_pipeline(TfidfVectorizer(),MultinomialNB())
+            model=gnb.fit(X, Y)
+            y_pred=model.predict(r)
+            y_pred=np.array(y_pred)
+            np.set_printoptions(threshold=np.inf)
+            t=np.array2string(y_pred.flatten(), precision=2, separator='\n',suppress_small=True)
+            f = open("test-A/out.tsv", "a")
+            f.write(t)