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vectorize text, and create sparse matrix and numpy array
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| import numpy as np | |
| import sklearn.feature_extraction.text as text | |
| vectorizer = text.CountVectorizer(input='filename', stop_words=my_stop_words, min_df=text_number) | |
| tm_sparse = vectorizer.fit_transform(texts) | |
| tm_array = vectorizer.fit_transform(texts).toarray() | |
| vocab = np.array(vectorizer.get_feature_names()) |
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