Closed huanfachen closed 4 years ago
Depends how you define "important". For permutation feature importance you can say that one feature causes more performance loss when permuted than another feature. I don't think there is a single clear definition of what importance in the context of model interpretation is.
Can we say 'one feature is more important than another' after comparing the feature importance? For example, using the absolute value of the t-statistic in linear regression. It sounds okay, but I would like to confirm this. Is there any literature on this?