Machine Learning-Based Surrogate Model for Genetic Algorithm with Aggressive Mutation for Feature Selection
Marc Chevallier,
Charly Clairmont
Abstract:The genetic algorithm with aggressive mutations GAAM, is a specialised algorithm for feature selection. This algorithm is dedicated to the selection of a small number of features and allows the user to specify the maximum number of features desired. A major obstacle to the use of this algorithm is its high computational cost, which increases significantly with the number of dimensions to be retained. To solve this problem, we introduce a surrogate model based on machine learning, which reduces the number of ev… Show more
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