A Recursive Partitioning Decision Rule for Nonparametric Classification
A Recursive Partitioning Decision Rule for Nonparametric Classification
A new criterion for deriving a recursive partitioning decision rule for nonparametric classification is presented. The criterion is both conceptually and computationally simple, and can be shown to have strong statistical merit. The resulting decision rule is asymptotically Bayes' risk efficient. The notion of adaptively generated features is introduced and …