Počet záznamů: 1
Fuzzy classification rules based on similarity
- 1.
SYSNO ASEP 0384879 Druh ASEP C - Konferenční příspěvek (mezinárodní konf.) Zařazení RIV D - Článek ve sborníku Název Fuzzy classification rules based on similarity Tvůrce(i) Holeňa, Martin (UIVT-O) SAI, RID
Štefka, D. (CZ)Zdroj.dok. Information Technologies - Applications and Theory. - Seňa : PONT s.r.o., 2012 / Horváth T. - ISBN 978-80-971144-0-4 Rozsah stran s. 25-31 Poč.str. 7 s. Forma vydání Online - E Akce ITAT 2012. Conference on Theory and Practice of Information Technologies Datum konání 17.09.2012-21.09.2012 Místo konání Ždiar Země SK - Slovensko Typ akce EUR Jazyk dok. eng - angličtina Země vyd. SK - Slovensko Klíč. slova classification rules ; fuzzy classification ; fuzzy integral ; fuzzy measure ; similarity Vědní obor RIV IN - Informatika CEP GA201/08/0802 GA ČR - Grantová agentura ČR Institucionální podpora UIVT-O - RVO:67985807 EID SCOPUS 84873925550 Anotace The paper deals with the aggregation of classification rules by means of fuzzy integrals, in particular with the fuzzy measures employed in that aggregation. It points out that the kinds of fuzzy measures commonly encountered in this context do not take into account the diversity of classification rules. As a remedy, a new kind of fuzzy measures is proposed, called similarity-aware measures, and several useful properties of such measures are proven. Finally, results of extensive experiments on a number of benchmark datasets are reported, in which a particular similarity-aware measure was applied to a combination of Choquet or Sugeno integrals with three different ways of creating ensembles of classification rules. In the experiments, the new measure was compared with the traditional Sugeno-measure, to which it was clearly superior. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2013
Počet záznamů: 1