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Multidimensional regression: How to make sure the error variances are the same along different dimensions? Should I be doing this?



Announcing the arrival of Valued Associate #679: Cesar Manara
Planned maintenance scheduled April 23, 2019 at 23:30 UTC (7:30pm US/Eastern)
2019 Moderator Election Q&A - Questionnaire
2019 Community Moderator Election ResultsRegression yields much smaller standard deviation and the mean is off, what could be wrong?How can I make a prediction in a regression model if a category has not been observed already?Is removing poorly predicted data points a valid approach?Validation of a model generated by automated deep learning systemInterpreting Results of Multivariable Regression / how to transform variables to improve resultsCNN only performs well when split into 2 modelsHow to attribute variance to an input parameter?Regression loss function is nanRegression variable colums (not all measures available)?How do I correctly build model on given data to predict target parameter?










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$begingroup$


I have data that has equal variance along each of the target dimensions, but if i analyze the results of training i notice that that my trained model does not have the same error variances along each of the dimensions, which means some dimensions are more erroneous than others.



Does this say anything about the model missing some sort of regularization, or is this not something I should be fretting over? Is there a way I can regularize to make sure the errors along different dimensions have the same variance?










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    0












    $begingroup$


    I have data that has equal variance along each of the target dimensions, but if i analyze the results of training i notice that that my trained model does not have the same error variances along each of the dimensions, which means some dimensions are more erroneous than others.



    Does this say anything about the model missing some sort of regularization, or is this not something I should be fretting over? Is there a way I can regularize to make sure the errors along different dimensions have the same variance?










    share|improve this question







    New contributor




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







    $endgroup$














      0












      0








      0





      $begingroup$


      I have data that has equal variance along each of the target dimensions, but if i analyze the results of training i notice that that my trained model does not have the same error variances along each of the dimensions, which means some dimensions are more erroneous than others.



      Does this say anything about the model missing some sort of regularization, or is this not something I should be fretting over? Is there a way I can regularize to make sure the errors along different dimensions have the same variance?










      share|improve this question







      New contributor




      journeymango 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 data that has equal variance along each of the target dimensions, but if i analyze the results of training i notice that that my trained model does not have the same error variances along each of the dimensions, which means some dimensions are more erroneous than others.



      Does this say anything about the model missing some sort of regularization, or is this not something I should be fretting over? Is there a way I can regularize to make sure the errors along different dimensions have the same variance?







      regression






      share|improve this question







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      journeymango 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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      journeymangojourneymango

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