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Diff for: unsupervised_class/tweets.py

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@@ -66,7 +66,7 @@ def filter_tweet(s):
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# transform the text into a data matrix
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tfidf = TfidfVectorizer(max_features=100, stop_words=stopwords)
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X = tfidf.fit_transform(text).todense()
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X = tfidf.fit_transform(text).asformat('array')
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# subsample for efficiency

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