Feature selection via binary simultaneous perturbation stochastic approximation
نویسندگان
چکیده
منابع مشابه
Feature selection via binary simultaneous perturbation stochastic approximation
Feature selection (FS) has become an indispensable task in dealing with today’s highly complex pattern recognition problems with massive number of features. In this study, we propose a new wrapper approach for FS based on binary simultaneous perturbation stochastic approximation (BSPSA). This pseudo-gradient descent stochastic algorithm starts with an initial feature vector and moves toward the...
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ژورنال
عنوان ژورنال: Pattern Recognition Letters
سال: 2016
ISSN: 0167-8655
DOI: 10.1016/j.patrec.2016.03.002