A Modified Memetic Algorithm with an Application to Gene Selection in a Sheep Body Weight Study.

ABSTRACT: Selecting the minimal best subset out of a huge number of factors for influencing the response is a fundamental and very challenging NP-hard problem because the presence of many redundant genes results in over-fitting easily while missing an important gene can more detrimental impact on predictions, and computation is prohibitive for exhaust search. We propose a modified memetic algorithm (MA) based on an improved splicing method to overcome the problems in the traditional genetic algorithm exploitation capability and dimension reduction in the predictor variables. The new algorithm accelerates the search in identifying the minimal best subset of genes by incorporating it into the new local search operator and hence improving the splicing method. The improvement is also due to another two

SUBMITTER: Miao M 

PROVIDER: S-EPMC8772977 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature