Feature Selection Algorithms: A Survey and Experimental Evaluation Luis Carlos Molina, Lluís Belanche, and Ŕngela Nebot   View Paper (PDF)   Return to Main-Track Regular Papers 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 us in certain situations. This work assess the performance of several fundamental algorithms found in the literature 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. This measure computer the degree of matching between the output given by the algorithm and the know optimal solution. Sample size effects are also studied. DiSC'03 © 2003 Association for Computing Machinery