Dynamic Classifier Aggregation using Fuzzy Integral with Interaction-Sensitive Fuzzy Measure

Result code in IS VaVaI
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Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Dynamic Classifier Aggregation using Fuzzy Integral with Interaction-Sensitive Fuzzy Measure
Original language description
In classifier combining, predictions of several classifiers are aggregated into a single prediction in order to improve the classification quality. Among others, fuzzy integrals are commonly used as aggregation operators. Usually, Sugeno lambda-measure is used as the fuzzy measure of the integral. However, interaction between the classifiers in the team (diversity), an important property in classifier combining, cannot be modeled by such fuzzy measure. In this paper, we present an interaction-sensitivefuzzy measure (ISFM), which can incorporate the diversity of the team into the aggregation process. Experimental results on 27 datasets show that the Choquet integral w.r.t. the ISFM outperforms the Choquet integral w.r.t. the Sugeno-lambda measure.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications
ISBN
978-1-4244-8135-4
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
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Publisher name
IEEE
Place of publication
Los Alamitos
Event location
Cairo
Event date
Nov 29, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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