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Decision Rule Classifiers for Multi-label Decision Tables
Conference proceeding   Peer reviewed

Decision Rule Classifiers for Multi-label Decision Tables

Fawaz Alsolami, Mohammad Azad, Igor Chikalov and Mikhail Moshkov
ROUGH SETS AND INTELLIGENT SYSTEMS PARADIGMS, RSEISP 2014, Vol.8537, pp.191-197
Lecture Notes in Computer Science
01/01/2014
DOI: https://doi.org/10.1007/978-3-319-08729-0_18

Abstract

Computer Science Computer Science, Artificial Intelligence Computer Science, Theory & Methods Logic Science & Technology Science & Technology - Other Topics Technology
Recently, multi-label classification problem has received significant attention in the research community. This paper is devoted to study the effect of the considered rule heuristic parameters on the generalization error. The results of experiments for decision tables from UCI Machine Learning Repository and KEEL Repository show that rule heuristics taking into account both coverage and uncertainty perform better than the strategies taking into account a single criterion.

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