To remove Chinese characters as features -












1












$begingroup$


I have created document-term matrix using TfIdfVectorizer, but just noticed the feature contains Chinese characters. Is it possible to remove them using Python's regex?



I believe these characters are one of reason for lower prediction accuracy of my model.



Currently I use the below for pre-processing my data-



   # Pre-processing the data

    def text_preprocess( data ):

        # Changing to lower case

        data = data.lower()

        # Removing special characters

        data = re.sub("(\d|\W)+"," ",data)

        return data


Also, please note I used stopwords='english' in my TfidfVectorizer.



Please let me know if any information required. (New here, still learning)






machine-learning python feature-extraction







share|improve this question









$endgroup$

















    1












    $begingroup$


    I have created document-term matrix using TfIdfVectorizer, but just noticed the feature contains Chinese characters. Is it possible to remove them using Python's regex?



    I believe these characters are one of reason for lower prediction accuracy of my model.



    Currently I use the below for pre-processing my data-



       # Pre-processing the data
    
    def text_preprocess( data ):
    
        # Changing to lower case
    
        data = data.lower()
    
        # Removing special characters
    
        data = re.sub("(\d|\W)+"," ",data)
    
        return data


    Also, please note I used stopwords='english' in my TfidfVectorizer.



    Please let me know if any information required. (New here, still learning)






    machine-learning python feature-extraction







    share|improve this question









    $endgroup$















      1












      1








      1





      $begingroup$


      I have created document-term matrix using TfIdfVectorizer, but just noticed the feature contains Chinese characters. Is it possible to remove them using Python's regex?



      I believe these characters are one of reason for lower prediction accuracy of my model.



      Currently I use the below for pre-processing my data-



         # Pre-processing the data
      
    def text_preprocess( data ):
      
        # Changing to lower case
      
        data = data.lower()
      
        # Removing special characters
      
        data = re.sub("(\d|\W)+"," ",data)
      
        return data


      Also, please note I used stopwords='english' in my TfidfVectorizer.



      Please let me know if any information required. (New here, still learning)






      machine-learning python feature-extraction







      share|improve this question









      $endgroup$




      I have created document-term matrix using TfIdfVectorizer, but just noticed the feature contains Chinese characters. Is it possible to remove them using Python's regex?



      I believe these characters are one of reason for lower prediction accuracy of my model.



      Currently I use the below for pre-processing my data-



         # Pre-processing the data
      
    def text_preprocess( data ):
      
        # Changing to lower case
      
        data = data.lower()
      
        # Removing special characters
      
        data = re.sub("(\d|\W)+"," ",data)
      
        return data


      Also, please note I used stopwords='english' in my TfidfVectorizer.



      Please let me know if any information required. (New here, still learning)






      machine-learning python feature-extraction




      machine-learning python feature-extraction






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked 2 days ago









      ranit.branit.b

      427




      427






















          1 Answer
          1






          active

          oldest

          votes


















          3












          $begingroup$

          If you want to remove non-English characters then this regex will work, by selecting characters not in a given ASCII range (0 to 122, you can adjust this since it will allow some special characters):



          ([^x00-x7A])+


          So to remove those characters:



          data = re.sub("([^x00-x7F])+"," ",data)





          share|improve this answer









          $endgroup$









          • 1




            $begingroup$
            Perfect. Even I was thinking on same line, like excluding all non-keyboard characters. But then realised, someone might have Chinese characters on their keyboards. :) You rightly pointed at the ASCII codes. Thanks.
            $endgroup$
            – ranit.b
            yesterday











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          1 Answer
          1






          active

          oldest

          votes









          active

          oldest

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          active

          oldest

          votes









          3












          $begingroup$

          If you want to remove non-English characters then this regex will work, by selecting characters not in a given ASCII range (0 to 122, you can adjust this since it will allow some special characters):



          ([^x00-x7A])+


          So to remove those characters:



          data = re.sub("([^x00-x7F])+"," ",data)





          share|improve this answer









          $endgroup$









          • 1




            $begingroup$
            Perfect. Even I was thinking on same line, like excluding all non-keyboard characters. But then realised, someone might have Chinese characters on their keyboards. :) You rightly pointed at the ASCII codes. Thanks.
            $endgroup$
            – ranit.b
            yesterday
















          3












          $begingroup$

          If you want to remove non-English characters then this regex will work, by selecting characters not in a given ASCII range (0 to 122, you can adjust this since it will allow some special characters):



          ([^x00-x7A])+


          So to remove those characters:



          data = re.sub("([^x00-x7F])+"," ",data)





          share|improve this answer









          $endgroup$









          • 1




            $begingroup$
            Perfect. Even I was thinking on same line, like excluding all non-keyboard characters. But then realised, someone might have Chinese characters on their keyboards. :) You rightly pointed at the ASCII codes. Thanks.
            $endgroup$
            – ranit.b
            yesterday














          3












          3








          3





          $begingroup$

          If you want to remove non-English characters then this regex will work, by selecting characters not in a given ASCII range (0 to 122, you can adjust this since it will allow some special characters):



          ([^x00-x7A])+


          So to remove those characters:



          data = re.sub("([^x00-x7F])+"," ",data)





          share|improve this answer









          $endgroup$



          If you want to remove non-English characters then this regex will work, by selecting characters not in a given ASCII range (0 to 122, you can adjust this since it will allow some special characters):



          ([^x00-x7A])+


          So to remove those characters:



          data = re.sub("([^x00-x7F])+"," ",data)






          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered yesterday









          Dan CarterDan Carter

          6451215




          6451215








          • 1




            $begingroup$
            Perfect. Even I was thinking on same line, like excluding all non-keyboard characters. But then realised, someone might have Chinese characters on their keyboards. :) You rightly pointed at the ASCII codes. Thanks.
            $endgroup$
            – ranit.b
            yesterday














          • 1




            $begingroup$
            Perfect. Even I was thinking on same line, like excluding all non-keyboard characters. But then realised, someone might have Chinese characters on their keyboards. :) You rightly pointed at the ASCII codes. Thanks.
            $endgroup$
            – ranit.b
            yesterday








          1




          1




          $begingroup$
          Perfect. Even I was thinking on same line, like excluding all non-keyboard characters. But then realised, someone might have Chinese characters on their keyboards. :) You rightly pointed at the ASCII codes. Thanks.
          $endgroup$
          – ranit.b
          yesterday




          $begingroup$
          Perfect. Even I was thinking on same line, like excluding all non-keyboard characters. But then realised, someone might have Chinese characters on their keyboards. :) You rightly pointed at the ASCII codes. Thanks.
          $endgroup$
          – ranit.b
          yesterday


















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