25 lines
941 B
Python
25 lines
941 B
Python
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from sklearn import preprocessing
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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 numpy as np
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eng = preprocessing.LabelEncoder()
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with open("train/in.tsv") as myFile:
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tmp = myFile.readlines()
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with open("train/expected.tsv") as finFile:
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fin = finFile.readlines()
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fin = eng.fit_transform(fin)
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with open("test-A/in.tsv") as tFile:
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fic = tFile.readlines()
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gnb = make_pipeline(TfidfVectorizer(),MultinomialNB())
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model = gnb.fit(tmp, fin)
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fin_pred = model.predict(fic)
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fin_pred = np.array(fin_pred)
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np.set_printoptions(threshold = np.inf)
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eFile = np.array2string(fin_pred.flatten(), precision = 2, separator = '\n',suppress_small = True)
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myFile = open("test-A/out.tsv", "a")
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myFile.write(eFile)
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