Feature selection in possibilistic modeling
We present a feature selection strategy for possibilitic modeling. We examine feature importance within one class and for classes?s discrimination. resolving conflict between feature?s importance using possibility uncertainty degree. Proposed strategy is able to handle data imperfection and gives good performances. Proposed strategy gives better and reliable results on any data set.
feature selection classes?s discrimination shapley index possibility theory possibility distribution uncertainty class representation