About: Multi-Objectivization and Surrogate Modelling for Neural Network Hyper-Parameters Tuning     Goto   Sponge   NotDistinct   Permalink

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Description
  • We present a multi-objectivization approach to the parameter tuning of RBF networks and multilayer perceptrons. The approach works by adding two new objectives - maximization of kappa statistic and minimization of root mean square error - to the originally single-objective problem of minimizing the classification error of the model. We show the performance of the multi-objectivization approach on five data sets and compare it to a surrogate based single-objective algorithm for the same problem. Moreover, we compare the multi-objectivization approach to two surrogate based approaches - a single-objective one and a multi-objective one.
  • We present a multi-objectivization approach to the parameter tuning of RBF networks and multilayer perceptrons. The approach works by adding two new objectives - maximization of kappa statistic and minimization of root mean square error - to the originally single-objective problem of minimizing the classification error of the model. We show the performance of the multi-objectivization approach on five data sets and compare it to a surrogate based single-objective algorithm for the same problem. Moreover, we compare the multi-objectivization approach to two surrogate based approaches - a single-objective one and a multi-objective one. (en)
Title
  • Multi-Objectivization and Surrogate Modelling for Neural Network Hyper-Parameters Tuning
  • Multi-Objectivization and Surrogate Modelling for Neural Network Hyper-Parameters Tuning (en)
skos:prefLabel
  • Multi-Objectivization and Surrogate Modelling for Neural Network Hyper-Parameters Tuning
  • Multi-Objectivization and Surrogate Modelling for Neural Network Hyper-Parameters Tuning (en)
skos:notation
  • RIV/67985807:_____/13:00428789!RIV15-AV0-67985807
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • I, P(LD13002), S
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
  • 90121
http://linked.open...ai/riv/idVysledku
  • RIV/67985807:_____/13:00428789
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • multi-objective optimization; parameter tuning; neural networks; surrogate modelling; multi-objectivization (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [FA09865F211F]
http://linked.open...v/mistoKonaniAkce
  • Nanning
http://linked.open...i/riv/mistoVydani
  • Berlin
http://linked.open...i/riv/nazevZdroje
  • Emerging Intelligent Computing Technology 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
  • Neruda, Roman
  • Pilát, M.
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 1865-0929
number of pages
http://bibframe.org/vocab/doi
  • 10.1007/978-3-642-39678-6_11
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 978-3-642-39677-9
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