To use UserId as a feature or not to train different ML Model












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Currently, I am working on electric load forecasting. Should I use userId as a feature to train one ML model or train as many models as a number of unique userID in the system (In this case automatically no need for userId as a feature)?



I think both are fine. In the first case as many numbers of dimension will be added as a unique feature this is fine too but I am not sure.



Machine learning model which I am currently looking is Random Forest, SVM etc. can anybody tell which approach is best.









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    $begingroup$


    Currently, I am working on electric load forecasting. Should I use userId as a feature to train one ML model or train as many models as a number of unique userID in the system (In this case automatically no need for userId as a feature)?



    I think both are fine. In the first case as many numbers of dimension will be added as a unique feature this is fine too but I am not sure.



    Machine learning model which I am currently looking is Random Forest, SVM etc. can anybody tell which approach is best.









    share







    New contributor




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







    $endgroup$















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      $begingroup$


      Currently, I am working on electric load forecasting. Should I use userId as a feature to train one ML model or train as many models as a number of unique userID in the system (In this case automatically no need for userId as a feature)?



      I think both are fine. In the first case as many numbers of dimension will be added as a unique feature this is fine too but I am not sure.



      Machine learning model which I am currently looking is Random Forest, SVM etc. can anybody tell which approach is best.









      share







      New contributor




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







      $endgroup$




      Currently, I am working on electric load forecasting. Should I use userId as a feature to train one ML model or train as many models as a number of unique userID in the system (In this case automatically no need for userId as a feature)?



      I think both are fine. In the first case as many numbers of dimension will be added as a unique feature this is fine too but I am not sure.



      Machine learning model which I am currently looking is Random Forest, SVM etc. can anybody tell which approach is best.







      machine-learning regression feature-selection decision-trees forecast





      share







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










      share







      New contributor




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








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      Ayush Mishra is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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      asked 9 mins ago









      Ayush MishraAyush Mishra

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