Partial covers, reducts and decision rules with weights

Mikhail Ju Moshkov, Marcin Piliszczuk, Beata Zielosko

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

In this chapter, we study the case, where each subset, used for covering, has its own weight, and we should minimize the total weight of subsets in partial cover. The same situation is with partial reducts and decision rules: each conditional attribute has its own weight, and we should minimize the total weight of attributes in partial reduct or decision rule. If weight of each attribute characterizes time complexity of attribute value computation, then we try to minimize total time complexity of computation of attributes from partial reduct or partial decision rule. If weight characterizes a risk of attribute value computation (as in medical or technical diagnosis), then we try to minimize total risk, etc. © 2008 Springer-Verlag Berlin Heidelberg.
Original languageEnglish (US)
Pages (from-to)51-96
Number of pages46
JournalStudies in Computational Intelligence
Volume145
DOIs
StatePublished - Sep 18 2008
Externally publishedYes

ASJC Scopus subject areas

  • Artificial Intelligence

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