Evaluating Feature Selection Algorithms

Authors:
Luis Carlos Molina;Lluís Belanche;Àngela Nebot
Affiliations:
-;-;-
Venue:
CCIA '02 Proceedings of the 5th Catalonian Conference on AI: Topics in Artificial Intelligence
Year:
2002

Citing 5
Cited 0

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Abstract

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 computes the degree of coincidence between the output given by the algorithm and the known optimal solution.