Floating search methods for feature selection with nonmonotonic criterion functions 论文

2002引用 351
Neural Networks and ApplicationsMetaheuristic Optimization Algorithms Research

摘要

In this paper the recently developed "floating search" algorithms are presented and modified to a more compact form facilitating their direct comparison with the well known (l,r) search. The properties of the floating search methods are investigated, especially with respect to their tolerance to nonmonotonic criteria. Their computational efficiency is demonstrated by results on real data of high dimensionality.