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Statements

Subject Item
n2:RIV%2F67985556%3A_____%2F09%3A00337780%21RIV10-MSM-67985556
rdf:type
skos:Concept n16:Vysledek
dcterms:description
Stability or robustness of feature selection methods is a topic of recent interest. A new stability measure based on the Shannon entropy is proposed in this paper to evaluate the overall occurrence of individual features in selected subsets of possibly varying cardinality. We compare the new measure to stability measures proposed recently by Somol et al. The new measure is computationally very efficient and adds another type of insight into the stability problem. All considered measures have been used to compare the stability of several feature selection methods (individually best ranking, sequential forward selection, sequential forward floating selection and dynamic oscillating search) on a set of examples. Stability or robustness of feature selection methods is a topic of recent interest. A new stability measure based on the Shannon entropy is proposed in this paper to evaluate the overall occurrence of individual features in selected subsets of possibly varying cardinality. We compare the new measure to stability measures proposed recently by Somol et al. The new measure is computationally very efficient and adds another type of insight into the stability problem. All considered measures have been used to compare the stability of several feature selection methods (individually best ranking, sequential forward selection, sequential forward floating selection and dynamic oscillating search) on a set of examples.
dcterms:title
A New Measure of Feature Selection Algorithms’ Stability A New Measure of Feature Selection Algorithms’ Stability
skos:prefLabel
A New Measure of Feature Selection Algorithms’ Stability A New Measure of Feature Selection Algorithms’ Stability
skos:notation
RIV/67985556:_____/09:00337780!RIV10-MSM-67985556
n3:aktivita
n18:P n18:Z
n3:aktivity
P(1ET400750407), P(1M0572), P(2C06019), P(GA102/07/1594), P(GA102/08/0593), Z(AV0Z10750506)
n3:dodaniDat
n10:2010
n3:domaciTvurceVysledku
n4:6617972 n4:4788575 n4:6956432
n3:druhVysledku
n14:D
n3:duvernostUdaju
n20:S
n3:entitaPredkladatele
n17:predkladatel
n3:idSjednocenehoVysledku
301398
n3:idVysledku
RIV/67985556:_____/09:00337780
n3:jazykVysledku
n13:eng
n3:klicovaSlova
feature selection; stability; measure
n3:klicoveSlovo
n8:stability n8:measure n8:feature%20selection
n3:kontrolniKodProRIV
[78E2DD011D43]
n3:mistoKonaniAkce
Miami, Florida
n3:mistoVydani
Washington, DC, USA
n3:nazevZdroje
ICDMW '09: Proceedings of the 2009 IEEE International Conference on Data Mining Workshops
n3:obor
n11:BD
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
3
n3:projekt
n7:2C06019 n7:GA102%2F08%2F0593 n7:1ET400750407 n7:GA102%2F07%2F1594 n7:1M0572
n3:rokUplatneniVysledku
n10:2009
n3:tvurceVysledku
Novovičová, Jana Somol, Petr Pudil, Pavel
n3:typAkce
n19:WRD
n3:zahajeniAkce
2009-12-06+01:00
n3:zamer
n21:AV0Z10750506
s:numberOfPages
6
n15:hasPublisher
IEEE Computer Society
n9:isbn
978-0-7695-3902-7