444463

run.py

@@ -0,0 +1,41 @@
+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.linear_model import LogisticRegression
+import lzma
+
+if __name__ == "__main__":
+    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"))
+    print("step 1")
+    with open('train/expected.tsv', 'r') as file:
+        for line in file:
+            line = line.strip()
+            Y.append(int(line))
+    print("step 2")
+    vectorizer = TfidfVectorizer()
+    X = vectorizer.fit_transform(X)
+
+    print("step 3")
+    model = LogisticRegression()
+    model.fit(X, Y)
+
+    print("step 4")
+    X_dev = []
+    Y_dev = []
+    with open('test-A/in.tsv', 'r') as file:
+        for line in file:
+            line = line.strip()
+            X_dev.append(line)
+
+    print("step 5")
+    X_dev = vectorizer.transform(X_dev)
+    prediction = model.predict(X_dev)
+
+    print("step 6")
+    f = open("test-A/out.tsv", "a")
+    for p in prediction:
+        f.write(str(p) + '\n')
+    f.close()