What is the interest to implement a statistics model in a groupby object instead of use the whole groups in a...












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I saw this topic and also this one in dask documentation.



I wonder what is the real interest to make a model for each group instead of considering a whole sample where all groups would appear? As far as I know the more informations you have, sure the more complexity you have (not good for overfitting), the more the trained model is fitting the reality. So what is the goal?
More precisely, after you answer the generality above, is it interesting to make odds ratio with a logistic regression where each model is applied on one group (excluding others in each model)? What are the pros, cons, then the limits?










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    $begingroup$


    I saw this topic and also this one in dask documentation.



    I wonder what is the real interest to make a model for each group instead of considering a whole sample where all groups would appear? As far as I know the more informations you have, sure the more complexity you have (not good for overfitting), the more the trained model is fitting the reality. So what is the goal?
    More precisely, after you answer the generality above, is it interesting to make odds ratio with a logistic regression where each model is applied on one group (excluding others in each model)? What are the pros, cons, then the limits?










    share|improve this question







    New contributor




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







    $endgroup$















      2












      2








      2





      $begingroup$


      I saw this topic and also this one in dask documentation.



      I wonder what is the real interest to make a model for each group instead of considering a whole sample where all groups would appear? As far as I know the more informations you have, sure the more complexity you have (not good for overfitting), the more the trained model is fitting the reality. So what is the goal?
      More precisely, after you answer the generality above, is it interesting to make odds ratio with a logistic regression where each model is applied on one group (excluding others in each model)? What are the pros, cons, then the limits?










      share|improve this question







      New contributor




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







      $endgroup$




      I saw this topic and also this one in dask documentation.



      I wonder what is the real interest to make a model for each group instead of considering a whole sample where all groups would appear? As far as I know the more informations you have, sure the more complexity you have (not good for overfitting), the more the trained model is fitting the reality. So what is the goal?
      More precisely, after you answer the generality above, is it interesting to make odds ratio with a logistic regression where each model is applied on one group (excluding others in each model)? What are the pros, cons, then the limits?







      data-mining machine-learning-model






      share|improve this question







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      Check out our Code of Conduct.











      share|improve this question







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      AvyWam is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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      asked 13 hours ago









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