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Journal articles
Empirical study of feature selection methods based on individual feature evaluation for classification problems
Abstract : The use of feature selection can improve accuracy, efficiency, applicability and understandability of a learning process and its resulting model. For this reason, many methods of automatic feature selection have been developed. By using a modularization of feature selection process, this paper evaluates a wide spectrum of these methods. The methods considered are created by combination of different selection criteria and individual feature evaluation modules. These methods are commonly used because of their low running time. After carrying out a thorough empirical study the most interesting methods are identified and some recommendations about which feature selection method should be used under different conditions are provided
https://hal-mines-paristech.archives-ouvertes.fr/hal-00614451
Contributor : Magalie Prudon Connect in order to contact the contributor
Submitted on : Thursday, August 11, 2011 - 2:30:57 PM
Last modification on : Wednesday, November 17, 2021 - 12:29:50 PM
Contributor : Magalie Prudon Connect in order to contact the contributor
Submitted on : Thursday, August 11, 2011 - 2:30:57 PM
Last modification on : Wednesday, November 17, 2021 - 12:29:50 PM