BOSO: A novel feature selection algorithm for linear regression with high-dimensional data.

ABSTRACT: With the frenetic growth of high-dimensional datasets in different biomedical domains, there is an urgent need to develop predictive methods able to deal with this complexity. Feature selection is a relevant strategy in machine learning to address this challenge. We introduce a novel feature selection algorithm for linear regression called BOSO (Bilevel Optimization Selector Operator). We conducted a benchmark of BOSO with key algorithms in the literature, finding a superior accuracy for feature selection in high-dimensional datasets. Proof-of-concept of BOSO for predicting drug sensitivity in cancer is presented. A detailed analysis is carried out for methotrexate, a well-studied drug targeting cancer metabolism.

SUBMITTER: Valcarcel LV 

PROVIDER: S-EPMC9187084 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature