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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F11%3A00175369%21RIV12-GA0-21230___
rdf:type
n14:Vysledek skos:Concept
rdfs:seeAlso
http://www.springerlink.com/content/e2187637114t4t75/
dcterms:description
We empirically confirm the hypothesis that the risk of overfitting (poor generalization) follows only from the number of model tests rather than the complexity of the selected model. We empirically confirm the hypothesis that the risk of overfitting (poor generalization) follows only from the number of model tests rather than the complexity of the selected model.
dcterms:title
An Experimental Test of Occam's Razor in Classification An Experimental Test of Occam's Razor in Classification
skos:prefLabel
An Experimental Test of Occam's Razor in Classification An Experimental Test of Occam's Razor in Classification
skos:notation
RIV/68407700:21230/11:00175369!RIV12-GA0-21230___
n14:predkladatel
n15:orjk%3A21230
n3:aktivita
n4:P
n3:aktivity
P(GAP103/10/1875)
n3:cisloPeriodika
3
n3:dodaniDat
n7:2012
n3:domaciTvurceVysledku
n16:4530314 n16:5523036
n3:druhVysledku
n20:J
n3:duvernostUdaju
n17:S
n3:entitaPredkladatele
n21:predkladatel
n3:idSjednocenehoVysledku
185475
n3:idVysledku
RIV/68407700:21230/11:00175369
n3:jazykVysledku
n6:eng
n3:klicovaSlova
Occam razor; Predictive Classification
n3:klicoveSlovo
n8:Predictive%20Classification n8:Occam%20razor
n3:kodStatuVydavatele
NL - Nizozemsko
n3:kontrolniKodProRIV
[C1403D03586E]
n3:nazevZdroje
Machine Learning
n3:obor
n18:JC
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n11:GAP103%2F10%2F1875
n3:rokUplatneniVysledku
n7:2011
n3:svazekPeriodika
82
n3:tvurceVysledku
Zahálka, Jan Železný, Filip
n3:wos
000288022900009
s:issn
0885-6125
s:numberOfPages
7
n19:doi
10.1007/s10994-010-5227-2
n5:organizacniJednotka
21230