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Statements

Subject Item
n2:RIV%2F68407700%3A21240%2F13%3A00196777%21RIV15-MSM-21240___
rdf:type
skos:Concept n17:Vysledek
rdfs:seeAlso
http://link.springer.com/chapter/10.1007/978-3-642-32922-7_3
dcterms:description
In the areas of Data Mining (DM) and Knowledge Discovery (KD), large variety of algorithms has been developed in the past decades, and the research is still ongoing. Data mining expertise is usually needed to deploy the algorithms available. Specifically, a process of interconnected actions referred to as knowledge flow (KF) needs to be assembled when the algorithms are to be applied to given data. In this paper, we propose an innovative evolutionary approach to automated KF synthesis and optimization. We demonstrate the evolutionary KF synthesis on the problem of classifier construction. Both preprocessing and machine learning actions are selected and configured by means of evolution to produce a model that fits very well for a given dataset. In the areas of Data Mining (DM) and Knowledge Discovery (KD), large variety of algorithms has been developed in the past decades, and the research is still ongoing. Data mining expertise is usually needed to deploy the algorithms available. Specifically, a process of interconnected actions referred to as knowledge flow (KF) needs to be assembled when the algorithms are to be applied to given data. In this paper, we propose an innovative evolutionary approach to automated KF synthesis and optimization. We demonstrate the evolutionary KF synthesis on the problem of classifier construction. Both preprocessing and machine learning actions are selected and configured by means of evolution to produce a model that fits very well for a given dataset.
dcterms:title
A Soft Computing Approach to Knowledge Flow Synthesis and Optimization A Soft Computing Approach to Knowledge Flow Synthesis and Optimization
skos:prefLabel
A Soft Computing Approach to Knowledge Flow Synthesis and Optimization A Soft Computing Approach to Knowledge Flow Synthesis and Optimization
skos:notation
RIV/68407700:21240/13:00196777!RIV15-MSM-21240___
n5:aktivita
n9:S
n5:aktivity
S
n5:dodaniDat
n7:2015
n5:domaciTvurceVysledku
n20:1266500 n20:9128336
n5:druhVysledku
n13:D
n5:duvernostUdaju
n22:S
n5:entitaPredkladatele
n21:predkladatel
n5:idSjednocenehoVysledku
59078
n5:idVysledku
RIV/68407700:21240/13:00196777
n5:jazykVysledku
n12:eng
n5:klicovaSlova
soft computing; knowledge discovery; evolutionary computation; embryonic graph evolution; genetic programming; process; directed acyclic graph
n5:klicoveSlovo
n6:evolutionary%20computation n6:genetic%20programming n6:embryonic%20graph%20evolution n6:directed%20acyclic%20graph n6:process n6:knowledge%20discovery n6:soft%20computing
n5:kontrolniKodProRIV
[CCA5AA3BDF29]
n5:mistoKonaniAkce
Ostrava
n5:mistoVydani
Heidelberg
n5:nazevZdroje
Soft Computing Models in Industrial and Environmental Applications
n5:obor
n11:IN
n5:pocetDomacichTvurcuVysledku
2
n5:pocetTvurcuVysledku
2
n5:rokUplatneniVysledku
n7:2013
n5:tvurceVysledku
Kordík, Pavel Řehořek, Tomáš
n5:typAkce
n16:EUR
n5:wos
000312974600003
n5:zahajeniAkce
2012-09-05+02:00
s:issn
2194-5357
s:numberOfPages
10
n19:doi
10.1007/978-3-642-32922-7_3
n18:hasPublisher
Springer-Verlag
n14:isbn
978-3-642-32921-0
n15:organizacniJednotka
21240