VIMs are not sufficient in capturing the patterns of dependency between features and response. They only reflect—in the form of a single number—the strength of this dependency. Partial dependence plots can be used to address this shortcoming. They can essentially be applied to any prediction method but are particularly useful for black-box methods which (in contrast to, say, generalized linear models) yield less interpretable results.
