Feature Subset Selection Using a Genetic Algorithm
dc.contributor.author | Yang, Jihoon | |
dc.contributor.author | Honavar, Vasant | |
dc.contributor.department | Computer Science | |
dc.date | 2018-02-13T23:12:24.000 | |
dc.date.accessioned | 2020-06-30T01:55:24Z | |
dc.date.available | 2020-06-30T01:55:24Z | |
dc.date.issued | 1997-05-03 | |
dc.description.abstract | <p>Practical pattern classification and knowledge discovery problems require selection of a subset of attributes or features (from a much larger set) to represent the patterns to be classified. This paper presents an approach to the multi-criteria optimization problem of feature subset selection using a genetic algorithm. Our experiments demonstrate the feasibility of this approach for feature subset selection in automated design of neural networks for pattern classification and knowledge discovery.</p> | |
dc.identifier | archive/lib.dr.iastate.edu/cs_techreports/156/ | |
dc.identifier.articleid | 1174 | |
dc.identifier.contextkey | 5409305 | |
dc.identifier.s3bucket | isulib-bepress-aws-west | |
dc.identifier.submissionpath | cs_techreports/156 | |
dc.identifier.uri | https://dr.lib.iastate.edu/handle/20.500.12876/19968 | |
dc.source.bitstream | archive/lib.dr.iastate.edu/cs_techreports/156/TR97_02a.pdf|||Fri Jan 14 20:43:30 UTC 2022 | |
dc.subject.disciplines | Artificial Intelligence and Robotics | |
dc.subject.disciplines | Programming Languages and Compilers | |
dc.subject.keywords | feature subset selection | |
dc.subject.keywords | genetic algorithms | |
dc.subject.keywords | constructive neural net learning algorithms | |
dc.title | Feature Subset Selection Using a Genetic Algorithm | |
dc.type | article | |
dc.type.genre | article | |
dspace.entity.type | Publication | |
relation.isOrgUnitOfPublication | f7be4eb9-d1d0-4081-859b-b15cee251456 |
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