Tinghuai Ma1,*, Honghao Zhou1, Dongdong Jia1, Abdullah Al-Dhelaan2, Mohammed Al-Dhelaan2, Yuan Tian3
CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.2, pp. 569-592, 2019, DOI:10.32604/cmes.2019.07758
Abstract Feature selection has been widely used in data mining and machine learning.
Its objective is to select a minimal subset of features according to some reasonable criteria
so as to solve the original task more quickly. In this article, a feature selection algorithm
with local search strategy based on the forest optimization algorithm, namely FSLSFOA,
is proposed. The novel local search strategy in local seeding process guarantees the quality
of the feature subset in the forest. Next, the fitness function is improved, which not only
considers the classification accuracy, but also considers the size of the feature subset. To
avoid… More >
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