Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 38, Issue 7, Pages 8170-8177Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2010.12.160
Keywords
Feature selection; Feature evaluation; Classification problems; Data reduction; Feature estimation
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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. (C) 2010 Elsevier Ltd. All rights reserved.
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