An artificial bee bare-bone hunger games search for global optimization and high-dimensional feature selection

ABSTRACT: Summary The domains of contemporary medicine and biology have generated substantial high-dimensional genetic data. Identifying representative genes and decreasing the dimensionality of the data can be challenging. The goal of gene selection is to minimize computing costs and enhance classification precision. Therefore, this article designs a new wrapper gene selection algorithm named artificial bee bare-bone hunger games search (ABHGS), which is the hunger games search (HGS) integrated with an artificial bee strategy and a Gaussian bare-bone structure to address this issue. To evaluate and validate the performance of our proposed method, ABHGS is compared to HGS and a single strategy embedded in HGS, six classic algorithms, and ten advanced algorithms on the CEC 2017 functions. The experim

SUBMITTER: Chen Z 

PROVIDER: S-EPMC10193239 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature