About: Correlation-based Feature Ranking in Combination with Embedded Feature Selection

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://iwim2009.felk.cvut.cz/files/ProceedingsIWIM09.pdf
Description	Most of Feature Ranking and Feature Selection approaches can be used for categorial data only. In this paper we present new methods for feature ranking and selection obtained as a combination of the above mentioned approaches. The data mining algorithm (GAME) is designed for numerical data, but it can be applied to categorial data as well. It incorporates feature selection mechanisms and new methods, proposed in this paper, derive feature ranking from final data mining model. The rank of each feature selected by model is computed by processing correlations of outputs between neighboring model's neurons in different ways. We used four different methods based on fuzzy logic, certainty factors and simple calculus. The performance of these four feature ranking methods was tested on artificial data sets and on well known real world data sets. These methods produce ranking consistent with recently published studies. Most of Feature Ranking and Feature Selection approaches can be used for categorial data only. In this paper we present new methods for feature ranking and selection obtained as a combination of the above mentioned approaches. The data mining algorithm (GAME) is designed for numerical data, but it can be applied to categorial data as well. It incorporates feature selection mechanisms and new methods, proposed in this paper, derive feature ranking from final data mining model. The rank of each feature selected by model is computed by processing correlations of outputs between neighboring model's neurons in different ways. We used four different methods based on fuzzy logic, certainty factors and simple calculus. The performance of these four feature ranking methods was tested on artificial data sets and on well known real world data sets. These methods produce ranking consistent with recently published studies. (en)
Title	Correlation-based Feature Ranking in Combination with Embedded Feature Selection Correlation-based Feature Ranking in Combination with Embedded Feature Selection (en)
skos:prefLabel	Correlation-based Feature Ranking in Combination with Embedded Feature Selection Correlation-based Feature Ranking in Combination with Embedded Feature Selection (en)
skos:notation	RIV/68407700:21240/09:00159293!RIV14-MSM-21240___
http://linked.open...avai/riv/aktivita	P Z
http://linked.open...avai/riv/aktivity	P(KJB201210701), Z(MSM6840770012)
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Kordík, Pavel
http://linked.open.../riv/druhVysledku	O - Ostatní výsledky nezařaditelné do žádného z výše uvedených druhů výsledku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	České vysoké učení technické v Praze / Fakulta informačních technologií
http://linked.open...dnocenehoVysledku	308410
http://linked.open...ai/riv/idVysledku	RIV/68407700:21240/09:00159293
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Feature Ranking; Feature Selection; Correlation; FAKE-GAME; Embedded Model. (en)
http://linked.open.../riv/klicoveSlovo	Feature Selection Embedded Model. Correlation FAKE-GAME Feature Ranking
http://linked.open...ontrolniKodProRIV	[7DD00C185708]
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	4 (xsd:int)
http://linked.open...vavai/riv/projekt	Automated Knowledge Extraction
http://linked.open...UplatneniVysledku	2009
http://linked.open...iv/tvurceVysledku	Pilný, Aleš Kordík, Pavel Šnorek, Miroslav Oertel, W.
http://linked.open...n/vavai/riv/zamer	Transdisciplinární výzkum v oblasti biomedicínského inženýrství II
http://localhost/t...ganizacniJednotka	21240

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