Feature selection based on the training set manipulation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F06%3A03124632" target="_blank" >RIV/68407700:21230/06:03124632 - 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
Feature selection based on the training set manipulation
Original language description
A novel filter feature selection technique is introduced. The method exploits the information conveyed by the evolution of the training samples weights similarly to the Adaboost algorithm. Features are selected on the basis of their individual merit using a simple error function. The weights dynamics and its effect on the error function are utilised to identify and remove redundant and irrelevant features. In experiments we show that the performance of commonly employed learning algorithms using features selected by the proposed method is the same or better than that obtained with features selected by the traditional state-of-theart techniques.
Czech name
Není k dispozici
Czech description
Není k dispozici

Project
<a href="/en/project/GA102%2F03%2F0440" target="_blank" >GA102/03/0440: Recognizing human activities for automated video surveillance</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2006
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
ICPR 2006: Proceedings of the 18th International Conference on Pattern Recognition
ISBN
0-7695-2521-0
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
658-661
Publisher name
IEEE Computer Society Press
Place of publication
Los Alamitos
Event location
Hongkong
Event date
Aug 20, 2006
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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