Clustering for variables with large amount of categories












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I have a dataset which, has variables with a lot of categories (some more than 1000). Since, large amount of categories effect the accuracy of the model. I saw some literature stating that if you do not have domain knowledge to group categories that have less than 5% of representation in the dataset.



My idea is that would it be possible to cluster these variables and will it make any sense to do so. For example if there are many variables which have a lot of categories it would be an issue to cluster one variable since as mentioned above the accuracy would be less because of the high number of categories in other variables.



Please let me know is this method valid.










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    -1












    $begingroup$


    I have a dataset which, has variables with a lot of categories (some more than 1000). Since, large amount of categories effect the accuracy of the model. I saw some literature stating that if you do not have domain knowledge to group categories that have less than 5% of representation in the dataset.



    My idea is that would it be possible to cluster these variables and will it make any sense to do so. For example if there are many variables which have a lot of categories it would be an issue to cluster one variable since as mentioned above the accuracy would be less because of the high number of categories in other variables.



    Please let me know is this method valid.










    share|improve this question









    New contributor




    Michael Schroter is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.







    $endgroup$















      -1












      -1








      -1





      $begingroup$


      I have a dataset which, has variables with a lot of categories (some more than 1000). Since, large amount of categories effect the accuracy of the model. I saw some literature stating that if you do not have domain knowledge to group categories that have less than 5% of representation in the dataset.



      My idea is that would it be possible to cluster these variables and will it make any sense to do so. For example if there are many variables which have a lot of categories it would be an issue to cluster one variable since as mentioned above the accuracy would be less because of the high number of categories in other variables.



      Please let me know is this method valid.










      share|improve this question









      New contributor




      Michael Schroter is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.







      $endgroup$




      I have a dataset which, has variables with a lot of categories (some more than 1000). Since, large amount of categories effect the accuracy of the model. I saw some literature stating that if you do not have domain knowledge to group categories that have less than 5% of representation in the dataset.



      My idea is that would it be possible to cluster these variables and will it make any sense to do so. For example if there are many variables which have a lot of categories it would be an issue to cluster one variable since as mentioned above the accuracy would be less because of the high number of categories in other variables.



      Please let me know is this method valid.







      clustering unsupervised-learning






      share|improve this question









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      Michael Schroter is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.











      share|improve this question









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      Michael Schroter is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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      share|improve this question




      share|improve this question








      edited 2 mins ago









      Anony-Mousse

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      5,155625






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      asked 1 hour ago









      Michael SchroterMichael Schroter

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