The binary version of this meta-heuristic optimizer is used for feature selection process through a wrapper based method. The Optimizer is set with a threshold value, provided they consider the random subset of data over each iteration and train the system and finally land up with minimum feature subset with best classification accuracy
☆10Jul 3, 2019Updated 7 years ago
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