Variable importance in Caret

Question

I am using the Caret package in R for training logistic regression model for a binary classification problem. I have been able to get the results, accuracy, etc., but I also want the importance of the variables (in decreasing order of importance). I used varImp() function. But according to the documentation, the importance depends on the class :

"For most classification models, each predictor will have a separate variable importance for each class (the exceptions are classification trees, bagged trees and boosted trees)."

How can I get the variable importance for each class ?

Thank you

Answer 1

For the first part, have you tried:

round(importance(myModel$finalModel), 2)

For putting that in decreasing order:

imp <- round(importance(myModel$finalModel), 2)
dfimp <- data.frame(feature = rownames(imp), MeanDecreaseGini = as.numeric(imp))
dfimp[order(dfimp$MeanDecreaseGini, decreasing = T),]