Dropped 2 Categories in Dummy Variables (Logistic Regression)

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I understand that when modeling, dummy variables should be k-1 and the dropped category should be the baseline. However, I do not know how to interpret if after feature selection 2 more categories of that dummy variable were removed (say I have a dummy variable with 5 categories - 1 would be the baseline, another 2 were removed after feature selection).



Should I still interpret it as usual, using the original dropped category as a baseline?






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    I understand that when modeling, dummy variables should be k-1 and the dropped category should be the baseline. However, I do not know how to interpret if after feature selection 2 more categories of that dummy variable were removed (say I have a dummy variable with 5 categories - 1 would be the baseline, another 2 were removed after feature selection).



    Should I still interpret it as usual, using the original dropped category as a baseline?






    logistic feature-selection categorical-encoding







    share|cite|improve this question

























      up vote
      1
      down vote

      favorite









      up vote
      1
      down vote

      favorite











      I understand that when modeling, dummy variables should be k-1 and the dropped category should be the baseline. However, I do not know how to interpret if after feature selection 2 more categories of that dummy variable were removed (say I have a dummy variable with 5 categories - 1 would be the baseline, another 2 were removed after feature selection).



      Should I still interpret it as usual, using the original dropped category as a baseline?






      logistic feature-selection categorical-encoding







      share|cite|improve this question















      I understand that when modeling, dummy variables should be k-1 and the dropped category should be the baseline. However, I do not know how to interpret if after feature selection 2 more categories of that dummy variable were removed (say I have a dummy variable with 5 categories - 1 would be the baseline, another 2 were removed after feature selection).



      Should I still interpret it as usual, using the original dropped category as a baseline?






      logistic feature-selection categorical-encoding




      logistic feature-selection categorical-encoding






      share|cite|improve this question















      share|cite|improve this question













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      share|cite|improve this question








      edited 2 hours ago









      kjetil b halvorsen

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      26.3k977189










      asked 3 hours ago









      SuperSaiyan

      163




      163




















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          You should think of the k-1 dummy variables as a "block" - either they all stay in the model or they are all eliminated from the model during the feature selection process. The reason for this is that the k-1 dummy variables together help encode the effect of the original categorical variable that spawned them.






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            Suppose 5 categories are A, B, C, D and E. Suppose that A is for baseline, and C and E were removed in the process of variable selection.



            It means A, C, and E have no statistically significant difference and they are combined into one group and treat A, C and E together as baseline.






            share|cite|improve this answer




















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              2 Answers
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              You should think of the k-1 dummy variables as a "block" - either they all stay in the model or they are all eliminated from the model during the feature selection process. The reason for this is that the k-1 dummy variables together help encode the effect of the original categorical variable that spawned them.






              share|cite|improve this answer
























                up vote
                2
                down vote













                You should think of the k-1 dummy variables as a "block" - either they all stay in the model or they are all eliminated from the model during the feature selection process. The reason for this is that the k-1 dummy variables together help encode the effect of the original categorical variable that spawned them.






                share|cite|improve this answer






















                  up vote
                  2
                  down vote










                  up vote
                  2
                  down vote









                  You should think of the k-1 dummy variables as a "block" - either they all stay in the model or they are all eliminated from the model during the feature selection process. The reason for this is that the k-1 dummy variables together help encode the effect of the original categorical variable that spawned them.






                  share|cite|improve this answer












                  You should think of the k-1 dummy variables as a "block" - either they all stay in the model or they are all eliminated from the model during the feature selection process. The reason for this is that the k-1 dummy variables together help encode the effect of the original categorical variable that spawned them.







                  share|cite|improve this answer












                  share|cite|improve this answer



                  share|cite|improve this answer










                  answered 3 hours ago









                  Isabella Ghement

                  4,433316




                  4,433316






















                      up vote
                      0
                      down vote













                      Suppose 5 categories are A, B, C, D and E. Suppose that A is for baseline, and C and E were removed in the process of variable selection.



                      It means A, C, and E have no statistically significant difference and they are combined into one group and treat A, C and E together as baseline.






                      share|cite|improve this answer
























                        up vote
                        0
                        down vote













                        Suppose 5 categories are A, B, C, D and E. Suppose that A is for baseline, and C and E were removed in the process of variable selection.



                        It means A, C, and E have no statistically significant difference and they are combined into one group and treat A, C and E together as baseline.






                        share|cite|improve this answer






















                          up vote
                          0
                          down vote










                          up vote
                          0
                          down vote









                          Suppose 5 categories are A, B, C, D and E. Suppose that A is for baseline, and C and E were removed in the process of variable selection.



                          It means A, C, and E have no statistically significant difference and they are combined into one group and treat A, C and E together as baseline.






                          share|cite|improve this answer












                          Suppose 5 categories are A, B, C, D and E. Suppose that A is for baseline, and C and E were removed in the process of variable selection.



                          It means A, C, and E have no statistically significant difference and they are combined into one group and treat A, C and E together as baseline.







                          share|cite|improve this answer












                          share|cite|improve this answer



                          share|cite|improve this answer










                          answered 3 hours ago









                          a_statistician

                          1,549139




                          1,549139



























                               

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