Dependence modeling rule mining using multi-objective genetic algorithms
| dc.contributor.author | Oliveira G.M.B.D. | |
| dc.contributor.author | Takiguti M.C.S. | |
| dc.contributor.author | Martins L.G.A. | |
| dc.date.accessioned | 2024-03-13T01:36:42Z | |
| dc.date.available | 2024-03-13T01:36:42Z | |
| dc.date.issued | 2008 | |
| dc.description.abstract | This work investigates the use of multi-objective genetic algorithms in the mining of accurate and interesting rules for the dependence modeling task. Dependence modeling is a generalization of the classification task in which a set of goal attributes is used. A multi-objective evolutionary environment named MO-miner was implemented based on the family of algorithms called non-dominated sorting genetic algorithms. Two desirable properties of the rules being mined - accuracy and interestingness - are simultaneously manipulated. MO-miner keeps the metrics related to these properties separated during the evolution, as different objectives used in the fitness calculus in a Pareto-based approach. The environment was applied to a public domain database named Nursery. The results obtained by MO-miner had been compared with those generated by a standard GA in order to identify the benefits related to the multi-objective approach. | |
| dc.description.firstpage | 278 | |
| dc.description.lastpage | 283 | |
| dc.identifier.uri | https://dspace.mackenzie.br/handle/10899/37473 | |
| dc.relation.ispartof | Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008 | |
| dc.rights | Acesso Restrito | |
| dc.subject.otherlanguage | And genetic algorithms | |
| dc.subject.otherlanguage | Artificial intelligence | |
| dc.subject.otherlanguage | Dependence modeling | |
| dc.subject.otherlanguage | Multi-objective | |
| dc.title | Dependence modeling rule mining using multi-objective genetic algorithms | |
| dc.type | Artigo de evento | |
| local.scopus.citations | 0 | |
| local.scopus.eid | 2-s2.0-62849097954 | |
| local.scopus.subject | And genetic algorithms | |
| local.scopus.subject | Classification tasks | |
| local.scopus.subject | Dependence modeling | |
| local.scopus.subject | Interesting rules | |
| local.scopus.subject | Interestingness | |
| local.scopus.subject | Multi-objective | |
| local.scopus.subject | Multi-objective genetic algorithms | |
| local.scopus.subject | Non-dominated sorting genetic algorithms | |
| local.scopus.subject | Public domains | |
| local.scopus.subject | Rule minings | |
| local.scopus.updated | 2024-05-01 | |
| local.scopus.url | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=62849097954&origin=inward |