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Evaluating feature selection algorithms

Autor
Molina, L.; Belanche, Ll.; Nebot, M.
Tipus d'activitat
Article en revista
Revista
Lecture notes in computer science
Data de publicació
2002-10
Volum
2504
Pàgina inicial
216
Pàgina final
227
DOI
https://doi.org/10.1007/3-540-36079-4_19 Obrir en finestra nova
URL
https://link.springer.com/chapter/10.1007/3-540-36079-4_19 Obrir en finestra nova
Resum
In view of the substantial number of existing feature selection algorithms, the need arises to count on criteria that enables to adequately decide which algorithm to use in certain situations. In this work a step is made is this direction by assessing the performance of several fundamental algorithms in a controlled scenario. A scoring measure ranks the algorithms by taking into account the amount of relevance, irrelevance and redundance on sample data sets of varying sizes. This measure compute...
Grup de recerca
IDEAI-UPC Intelligent Data Science and Artificial Intelligence
SOCO - Soft Computing

Participants