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Chapter

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Title

Multi-objective Search for Comprehensible Rule Ensembles

Authors

[ 1 ] Instytut Informatyki, Wydział Informatyki, Politechnika Poznańska | [ P ] employee

Year of publication

2016

Chapter type

paper

Publication language

english

Keywords
EN
  • rule ensembles
  • classification
  • regularization
  • Variable-consistency Dominance-based Rough Set Approach (VC-DRSA)
Abstract

EN We present a methodology for constructing an ensemble of rule base classifiers characterized not only by a good accuracy of classification but also by a good quality of knowledge representation. The base classifiers forming the ensemble are composed of minimal sets of rules that cover training objects, while being relevant for their high support, low anti-support and high Bayesian confirmation measure. The population of base classifiers is evolving in course of a bi-objective optimization procedure that involves accuracy of classification and diversity of base classifiers. The final population constitutes an ensemble classifier enjoying some desirable properties, as shown in a computational experiment.

Pages (from - to)

503 - 513

DOI

10.1007/978-3-319-47160-0_46

URL

https://link.springer.com/chapter/10.1007/978-3-319-47160-0_46

Book

Rough Sets : International Joint Conference, IJCRS 2016, Santiago de Chile, Chile, October 7–11, 2016 : Proceedings

Presented on

International Joint Conference on Rough Sets, IJCRS 2016, 7-11.10.2016, Santiago de Chile, Chile

Publication indexed in

WoS (15)

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