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Dynamic Classifier Aggregation using Interaction-Sensitive Fuzzy Measures
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SYSNO ASEP 0442868 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název Dynamic Classifier Aggregation using Interaction-Sensitive Fuzzy Measures Tvůrce(i) Štefka, D. (CZ)
Holeňa, Martin (UIVT-O) SAI, RIDZdroj.dok. Fuzzy Sets and Systems. - : Elsevier - ISSN 0165-0114
Roč. 270, 1 July (2015), s. 25-52Poč.str. 28 s. Jazyk dok. eng - angličtina Země vyd. NL - Nizozemsko Klíč. slova Fuzzy integral ; Fuzzy measure ; Dynamic classifier aggregation Vědní obor RIV IN - Informatika CEP GA13-17187S GA ČR - Grantová agentura ČR Institucionální podpora UIVT-O - RVO:67985807 UT WOS 000352208900002 EID SCOPUS 84926246510 DOI 10.1016/j.fss.2014.09.005 Anotace In classifier aggregation using fuzzy integral, the performance of the classifier system depends heavily on the choice of the underlying fuzzy measure. However, little attention has been given to the choice of the fuzzy measure in the literature; usually, the Sugeno lambda-measure is used. A weakness of the Sugeno lambda-measure is that it cannot model the interactions between individual classifiers. That motivated us to develop two novel fuzzy measures and a modification of an existing fuzzy measure which are interaction-sensitive, i.e., they model not only the confidences of classifiers, but also their mutual similarities. The properties of the measures are first studied theoretically, and in the experimental section, the performance of the proposed measures is compared to the traditionally used additive measure and Sugeno lambda-measure. Experiments on 23 benchmark datasets and 3 different classifier systems show that the interaction-sensitive fuzzy measures clearly outperform their non-interaction sensitive counterparts. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2016
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