Bayes2 solution

bayes.py

@@ -0,0 +1,24 @@
+import pandas as pd
+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.naive_bayes import MultinomialNB
+from sklearn.pipeline import make_pipeline
+
+df = pd.read_csv("train/train.tsv", error_bad_lines=False, header=None, sep="\t")
+dev0 = pd.read_csv("dev-0/in.tsv", header=None, sep="\t")
+testA = pd.read_csv("test-A/in.tsv", header=None, sep="\t")
+
+dev0X = dev0.iloc[:, 0].tolist()
+testAX = testA.iloc[:, 0].tolist()
+
+Y = df.iloc[:, 0].tolist()
+X = df.iloc[:, 1].tolist()
+
+model = make_pipeline(TfidfVectorizer(), MultinomialNB())
+
+model.fit(X, Y)
+
+dev0_predicted = model.predict(dev0X)
+testA_predicted = model.predict(testAX)
+
+pd.Series(dev0_predicted).to_csv("dev-0/out.tsv", sep="\t", index=False, header=False)
+pd.Series(testA_predicted).to_csv("test-A/out.tsv", sep="\t", index=False, header=False)