Criteria Ensembles in Feature Selection

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F09%3A00326643" target="_blank" >RIV/67985556:_____/09:00326643 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Criteria Ensembles in Feature Selection

Original language description

In feature selection the effect of over-fitting may lead to serious degradation of generalization ability. We introduce the concept of combining multiple feature selection criteria in feature selection methods with the aim to obtain feature subsets thatgeneralize better. The concept is applicable with many existing feature selection methods. Here we discuss in more detail the family of sequential search methods. The concept does not specify which criteria to combine ? to illustrate its feasibility we give a simple example of combining the estimated accuracy of k-nearest neighbor classifiers for various k.We perform the experiments on a number of datasets. The potential to improve is clearly seen on improved classifier performance on independent test data as well as on improved feature selection stability.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

BD - Information theory

OECD FORD branch

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Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2009

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Multiple Classifier Systems, LNCS 5519

ISBN

3-642-02325-8

ISSN

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e-ISSN

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Number of pages

10

Pages from-to

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Publisher name

Springer

Place of publication

Berlin Heidelberg

Event location

Reykjavik

Event date

Jun 10, 2009

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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