Work

Learning feature spaces for regression with genetic programming

Year: 2020

Type: article

Source: Genetic Programming and Evolvable Machines

DOI: 10.1007/s10710-020-09383-4

Authors: William La Cava, Jason H. Moore

Institution: University of Pennsylvania

Language: English

Topic: Evolutionary Algorithms and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: Pennsylvania Department of Health, National Institutes of Health, National Institute of Allergy and Infectious Diseases, U.S. National Library of Medicine

Awards: G1080356687, G1210767767, G142613954, Multi-objective representation learning methods for interpetable predictions of patient outcomesusing electronic health records, G2229312748, G2931470801, Biomedical Computing and Informatics Strategies for Infectious Disease Research, G513283357, G886040649, G9000155670

OpenAlex ID: W3012187195

FWCI: 2.693

Cites: 76

Cited by: 39

Related to: 10