18 lines
653 B
Python
18 lines
653 B
Python
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import sklearn.metrics
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from sklearn.cluster import KMeans
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from sklearn.feature_extraction.text import TfidfVectorizer
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import numpy as np
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with open("test-A/in.tsv") as myFile:
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cnt = myFile.readlines()
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vect = TfidfVectorizer(ngram_range = (1,2), use_idf = False)
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vect = TfidfVectorizer()
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document_vectors = vect.fit_transform(cnt)
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kmeans = KMeans(n_clusters = 77, random_state = 0).fit(document_vectors)
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pred_myFile = kmeans.fit_predict(document_vectors)
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tmp = kmeans.labels_
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tmp = np.array2string(tmp, precision = 2, separator = '\n',suppress_small = True)
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myFile = open("test-A/out.tsv", "a")
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myFile.write(tmp)
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