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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-sensitive fuzzy 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.
  • 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-sensitive fuzzy 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. (en)
Title
  • Dynamic Classifier Aggregation using Fuzzy Integral with Interaction-Sensitive Fuzzy Measure
  • Dynamic Classifier Aggregation using Fuzzy Integral with Interaction-Sensitive Fuzzy Measure (en)
skos:prefLabel
  • Dynamic Classifier Aggregation using Fuzzy Integral with Interaction-Sensitive Fuzzy Measure
  • Dynamic Classifier Aggregation using Fuzzy Integral with Interaction-Sensitive Fuzzy Measure (en)
skos:notation
  • RIV/67985807:_____/10:00351614!RIV11-GA0-67985807
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA201/08/0802), P(ME 949), Z(AV0Z10300504)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 255481
http://linked.open...ai/riv/idVysledku
  • RIV/67985807:_____/10:00351614
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • dynamic classifier combining; fuzzy integral; Choquet integral; fuzzy measure (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [5C9D5ED330D1]
http://linked.open...v/mistoKonaniAkce
  • Cairo
http://linked.open...i/riv/mistoVydani
  • Los Alamitos
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Holeňa, Martin
  • Štefka, David
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • IEEE
https://schema.org/isbn
  • 978-1-4244-8135-4
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