Skip to main content
Cross Validated

Return to Answer

my answer was based on how varimp_plot() method treated glm (originally under the hood it would switch to std_coef_plot(). This treatment has been changed since variable importance was added for GLM.
Source Link
Lauren
Lauren
  • 251
  • 1
  • 5

Please use h2o.coef_norm() insteadThe relative importance is based on the coefficients, the scaled importance is the relative importance scaled between 0 and 1. When applied to a GLM model h2o.varimp() should simply returnYou can see the normalized coefficients for comparison by using h2o.coef_norm(), but it looks like it doesn't (this is a bug). Please note this was fixed for the Python API but may not have been fixed yet for the R API.

Please use h2o.coef_norm() instead. When applied to a GLM model h2o.varimp() should simply return h2o.coef_norm(), but it looks like it doesn't (this is a bug). Please note this was fixed for the Python API but may not have been fixed yet for the R API.

The relative importance is based on the coefficients, the scaled importance is the relative importance scaled between 0 and 1. You can see the normalized coefficients for comparison by using h2o.coef_norm().

Source Link
Lauren
Lauren
  • 251
  • 1
  • 5

Please use h2o.coef_norm() instead. When applied to a GLM model h2o.varimp() should simply return h2o.coef_norm(), but it looks like it doesn't (this is a bug). Please note this was fixed for the Python API but may not have been fixed yet for the R API.