An Efficient Parallel Reptile Search Algorithm and Snake Optimizer Approach for Feature Selection
An Efficient Parallel Reptile Search Algorithm and Snake Optimizer Approach for Feature Selection
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Basel: MDPI AG
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Language
English
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Basel: MDPI AG
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Feature Selection (FS) is a major preprocessing stage which aims to improve Machine Learning (ML) models’ performance by choosing salient features, while reducing the computational cost. Several approaches are presented to select the most Optimal Features Subset (OFS) in a given dataset. In this paper, we introduce an FS-based approach named Reptil...
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An Efficient Parallel Reptile Search Algorithm and Snake Optimizer Approach for Feature Selection
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TN_cdi_doaj_primary_oai_doaj_org_article_6de8b9e043a646b093d5303419238707
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6de8b9e043a646b093d5303419238707
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ISSN
2227-7390
E-ISSN
2227-7390
DOI
10.3390/math10132351
