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naive-baye
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dev-0/out.tsv
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dev-0/out.tsv
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run.py
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run.py
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from sklearn.feature_extraction.text import TfidfVectorizer
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from sklearn.naive_bayes import MultinomialNB
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from sklearn.pipeline import make_pipeline
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import sys
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import pandas as pd
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train_file = sys.argv[1]
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pred_x_file = sys.argv[2]
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train = pd.read_csv(train_file, sep='\t', header=None)
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pred_x = pd.read_csv(pred_x_file, sep='\t', header=None)
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train_x, train_y = train[1], train[0]
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model = make_pipeline(TfidfVectorizer(), MultinomialNB())
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model.fit(train_x, train_y)
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pred_y = model.predict(pred_x.stack())
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pd.DataFrame(pred_y).to_csv('out.tsv', header=False, index=None)
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test-A/out.tsv
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test-A/out.tsv
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