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Description
  • Není k dispozici (cs)
  • This paper presents an algorithm for induction of ensembles of decision trees, also referred to as decision forests. In order to achieve high expressiveness the trees induced are multivariate, with various, possibly user-defined tests in their internal nodes. Strongly typed genetic programming is utilized to evolve structure of the tests. Special attention is given to the problem of diversity of the forest constructed. An approach is proposed, which explicitly encourages the induction algorithm to produce a different tree each run, which represents an alternative description of the data. It is shown that forests constructed this way have significantly reduced classification error even for small forest size, compared to other ensemble methods. Classification accuracy is also compared to other recent methods on several real-world datasets.
  • This paper presents an algorithm for induction of ensembles of decision trees, also referred to as decision forests. In order to achieve high expressiveness the trees induced are multivariate, with various, possibly user-defined tests in their internal nodes. Strongly typed genetic programming is utilized to evolve structure of the tests. Special attention is given to the problem of diversity of the forest constructed. An approach is proposed, which explicitly encourages the induction algorithm to produce a different tree each run, which represents an alternative description of the data. It is shown that forests constructed this way have significantly reduced classification error even for small forest size, compared to other ensemble methods. Classification accuracy is also compared to other recent methods on several real-world datasets. (en)
Title
  • Inducing Diverse Decision Forests with Genetic Programming
  • Není k dispozici (cs)
  • Inducing Diverse Decision Forests with Genetic Programming (en)
skos:prefLabel
  • Inducing Diverse Decision Forests with Genetic Programming
  • Není k dispozici (cs)
  • Inducing Diverse Decision Forests with Genetic Programming (en)
skos:notation
  • RIV/68407700:21230/05:03107899!RIV06-AV0-21230___
http://linked.open.../vavai/riv/strany
  • 301 ; 310
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1ET201210527)
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
  • 524587
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/05:03107899
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Genetic Programming; decision forests; decision trees (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [916C596A6AFC]
http://linked.open...v/mistoKonaniAkce
  • Lausanne
http://linked.open...i/riv/mistoVydani
  • Heidelberg
http://linked.open...i/riv/nazevZdroje
  • Genetic Programming
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
  • Kubalík, Jiří
  • Suchý, Jan
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 3-540-25436-6
http://localhost/t...ganizacniJednotka
  • 21230
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