Improving logistic regression classification of credit approval with features constructed by kaizen programming
| dc.contributor.author | de Melo, Vinicius Veloso [UNIFESP] | |
| dc.contributor.author | Banzhaf, Wolfgang | |
| dc.date.accessioned | 2019-01-21T10:29:48Z | |
| dc.date.available | 2019-01-21T10:29:48Z | |
| dc.date.issued | 2016 | |
| dc.description.abstract | In this contribution, we employ the recently proposed Kaizen Programming (KP) approach to fi nd high-quality nonlinear combinations of the original features in a dataset. KP constructs many complementary features at the same time, which are selected by their importance, not by model quality. We investigated our approach in a well-known realworld credit scoring dataset. When compared to related approaches, KP reaches similar or better results, but evaluates fewer models. | en |
| dc.description.affiliation | Institute of Science and Technology (ICT) Federal University of São Paulo (UNIFESP) São José dos Campos, SP, Brazill | |
| dc.description.affiliation | Department of Computer Science Memorial University of Newfoundland St. John’s, NL, A1B 3X5, Canada | |
| dc.description.affiliationUnifesp | Institute of Science and Technology (ICT) Federal University of São Paulo (UNIFESP) São José dos Campos, SP, Brazil | |
| dc.description.source | Web of Science | |
| dc.format.extent | 61-62 | |
| dc.identifier | http://dx.doi.org/10.1145/2908961.2908963 | |
| dc.identifier.citation | Proceedings Of The 2016 Genetic And Evolutionary Computation Conference (GECCO'16 Companion). New york, p. 61-62, 2016. | |
| dc.identifier.doi | 10.1145/2908961.2908963 | |
| dc.identifier.uri | http://repositorio.unifesp.br/handle/11600/49401 | |
| dc.identifier.wos | WOS:000383741800031 | |
| dc.language.iso | eng | |
| dc.publisher | Funpec-Editora | |
| dc.relation.ispartof | Proceedings Of The 2016 Genetic And Evolutionary Computation Conference (GECCO'16 Companion) | |
| dc.rights | info:eu-repo/semantics/restrictedAccess | |
| dc.subject | Credit Approval | en |
| dc.subject | Logistic Regression | en |
| dc.subject | Classification | en |
| dc.subject | Kaizen Programming | en |
| dc.title | Improving logistic regression classification of credit approval with features constructed by kaizen programming | en |
| dc.type | info:eu-repo/semantics/conferenceObject |