first sollution by bayes

run.py

@@ -0,0 +1,57 @@
+from naivebayes import NaiveBayesTextClassifier
+import lzma
+from spacy.lang.en.stop_words import STOP_WORDS as en_stop
+
+categories_list = [0, 1]
+
+classifier = NaiveBayesTextClassifier(
+    categories=categories_list,
+    stop_words=en_stop
+)
+
+X = []
+Y = []
+with lzma.open('train/in.tsv.xz', 'r') as file:
+    for line in file:
+        line = line.strip()
+        X.append(line.decode("utf-8"))
+
+
+with open('train/expected.tsv', 'r') as file:
+    for line in file:
+        line = line.strip()
+        Y.append(int(line))
+print(len(X), len(Y))
+classifier.train(X[:15000], Y[:15000])
+classifier.train(X[15000:30000], Y[15000:30000])
+# classifier.train(X[30000:60000], Y[30000:60000])l
+# classifier.train(X[60000:90000], Y[60000:90000])
+
+
+test_x = []
+with lzma.open('dev-0/in.tsv.xz', 'r') as file:
+    for line in file:
+        line = line.strip()
+        test_x.append(line.decode("utf-8"))
+
+predicted_classes = classifier.classify(test_x)
+
+
+f = open("dev-0/out.tsv", "a")
+for p in predicted_classes:
+    f.write(str(p) + '\n')
+f.close()
+
+test_x = []
+with lzma.open('test-A/in.tsv.xz', 'r') as file:
+    for line in file:
+        line = line.strip()
+        test_x.append(line.decode("utf-8"))
+
+predicted_classes = classifier.classify(test_x)
+
+
+f = open("test-A/out.tsv", "a")
+for p in predicted_classes:
+    f.write(str(p) + '\n')
+f.close()