Have you checked that your other program tokenizes the same way as the default sklearn tokenization?
On 19 November 2015 at 11:09, Ehsan Asgari <asg...@berkeley.edu> wrote: > Hi, > > Thank you, but it didn't work. > I checked len(tf.vocabulary_) and it is also 1900 instead of 1914. > I have another program that counts distinct terms and it is 1914 there. > > Best, > Ehsan > > > > On Thu, Nov 19, 2015 at 9:36 AM, Andreas Mueller <t3k...@gmail.com> wrote: > >> You should set min_df=1 and max_df=1.0 (which should be the default, but >> it depends on your scikit-learn version). >> How did you determine that your vocabulary size should be 1860? >> >> >> >> On 11/19/2015 12:31 PM, Ehsan Asgari wrote: >> >> Hi, >> >> Thank you for your reply. I changed my delimeters from tab to space and >> most of the problem has been solved (1900 index term from 1914). However, >> still there are few words that are excluded. I didn't set any parameter as >> you can see in the code. >> >> tf = TfidfVectorizer(ngram_range=(1,ngram),use_idf=False) >>> tf_matrix = tf.fit_transform(corpus) >>> feature_names = tf.get_feature_names() >>> >>> Should I play with the min_df and max_df? >> >> Best, >> Ehsan >> >> On Nov 19, 2015, at 9:01 AM, Chris Holdgraf < <choldg...@berkeley.edu> >> choldg...@berkeley.edu> wrote: >> >> If you vocab is indeed being cut down, could it be because some words >> don't pass through the word frequency cutoff filters? (min_df, max_df) >> >> On Thu, Nov 19, 2015 at 8:55 AM, Andreas Mueller < <t3k...@gmail.com> >> t3k...@gmail.com> wrote: >> >>> Hi Ehsan. >>> Which version of scikit-learn are you using? >>> And why do you think the vocabulary size is 1860? >>> What is len(tf.vocabulary_)? >>> >>> Andy >>> >>> On 11/18/2015 11:45 PM, Ehsan Asgari wrote: >>> >>> Hi, >>> >>> I am using TfidfVectorizer of sklearn.feature_extraction.text for >>> generating tf-idf matrix of a corpus. However, when I look at the features >>> extracted from my corpus it seems that it has reduced my vocabulary size >>> from 1860 to 598! I tried to play with max_df, min_df, and max_features. >>> But nothing changed. >>> >>> tf = TfidfVectorizer(ngram_range=(1,ngram),use_idf=False) >>> tf_matrix = tf.fit_transform(corpus) >>> feature_names = tf.get_feature_names() >>> >>> Does someone have an idea how to solve this problem? >>> >>> Thank you, >>> >>> Ehsan >>> >>> >>> >>> >>> ------------------------------------------------------------------------------ >>> >>> >>> >>> _______________________________________________ >>> Scikit-learn-general mailing >>> listScikit-learn-general@lists.sourceforge.nethttps://lists.sourceforge.net/lists/listinfo/scikit-learn-general >>> >>> >>> >>> >>> ------------------------------------------------------------------------------ >>> >>> _______________________________________________ >>> Scikit-learn-general mailing list >>> Scikit-learn-general@lists.sourceforge.net >>> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >>> >>> >> >> >> -- >> _____________________________________ >> >> PhD Candidate in Neuroscience | UC Berkeley <http://hwni.org/> >> Editor and Web Director | Berkeley Science Review >> <http://sciencereview.berkeley.edu/> >> _____________________________________ >> >> >> ------------------------------------------------------------------------------ >> >> _______________________________________________ >> Scikit-learn-general mailing list >> Scikit-learn-general@lists.sourceforge.net >> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >> >> >> >> ------------------------------------------------------------------------------ >> >> >> >> _______________________________________________ >> Scikit-learn-general mailing >> listScikit-learn-general@lists.sourceforge.nethttps://lists.sourceforge.net/lists/listinfo/scikit-learn-general >> >> >> >> >> ------------------------------------------------------------------------------ >> >> _______________________________________________ >> Scikit-learn-general mailing list >> Scikit-learn-general@lists.sourceforge.net >> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >> >> > > > ------------------------------------------------------------------------------ > > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > >
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