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Method of Static Classifiers Selection Using the Weights of Base Classifiers

  • Robert BurdukEmail author
Chapter
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 342)

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.

Keywords

Classifier fusion Interval logic Static classifiers selection Multiple classifier system 

Notes

Acknowledgments

This work was supported by the Polish National Science Center under the grant no. DEC-2013/09/B/ST6/02264 and by the statutory funds of the Department of Systems and Computer Networks, Wroclaw University of Technology.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Systems and Computer NetworksWroclaw University of TechnologyWroclawPoland

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