def ngramBOW(data, cols=None, min_gram=1, max_gram=1, min_df=3, max_df=1.0, 
             lowercase=True, strip_accents='unicode', stop_words=None, 
             token_pattern=u'(?u)\b\w\w+\b'):
    count_vect = feature_extraction.text.CountVectorizer(min_df=min_df, 
                    max_df=max_df, ngram_range=(min_gram,max_gram), binary=True,
                    lowercase=lowercase, stop_words=stop_words, 
                    strip_accents=strip_accents, token_pattern=token_pattern,
                    charset_error='replace')
    return count_vect.fit_transform(data)
Required.
dataset/ETHPy150Open theusual/kaggle-seeclickfix-ensemble/Miroslaw/data_transforms.py/ngramBOW--crossover with--dataset/ETHPy150Open saltstack/salt/salt/proxy/ssh_sample.py/ping