Method of static classifiers selection using theweights of base classifiers

Abstract

The choice of a pertinent objective function is one of the most crucial elements in static ensemble selection. In this study, a new approach of calculating the weight of base classifiers is developed. The values of these weights are the basis for the selection process of classifiers from the initial pool. The obtained weights are interpreted in the context of the interval logic. A number of experiments have been carried out on several datasets available in the UCI repository. The performed experiments compare the proposed algorithms with base classifiers, oracle, sum, product, and mean methods.