A COMPARATIVE EVALUATION OF MEDIUM-AND LARGE-SCALE FEATURE SELECTORS FOR PATTERN CLASSIFIERS
Mineichi Kudo, Jack Sklansky · Czech digital mathematics library · 1998
Needs of feature selection in medium and large problems (medium- and large-scale feature selection) increases in many fields including medical and image processing fields. Previous comparative studies of feature selection algorithms are not sufficient in problem size and in criterion function. In addition, no way has not shown to compare algorithms with different objectives. In this study, we propose a unified way to compare a large variety of algorithms. Our results on some medium and large problems show that the sequential floating algorithms promises for up to medium problems and genetic algorithms for medium and large problems.