An attribute-centre based decision tree classification algorithm
| dc.contributor.author | Silahtaro?lu G. | |
| dc.date.accessioned | 2024-03-13T10:01:30Z | |
| dc.date.available | 2024-03-13T10:01:30Z | |
| dc.date.issued | 2009 | |
| dc.department | İstanbul Beykent Üniversitesi | en_US |
| dc.description.abstract | Decision tree algorithms have very important place at classification model of data mining. In literature, algorithms use entropy concept or gini index to form the tree. The shape of the classes and their closeness to each other some of the factors that affect the performance of the algorithm. In this paper we introduce a new decision tree algorithm which employs data (attribute) folding method and variation of the class variables over the branches to be created. A comparative performance analysis has been held between the proposed algorithm and C4.5. | en_US |
| dc.identifier.endpage | 306 | en_US |
| dc.identifier.issn | 2010-376X | |
| dc.identifier.scopus | 2-s2.0-78651560851 | en_US |
| dc.identifier.scopusquality | N/A | en_US |
| dc.identifier.startpage | 302 | en_US |
| dc.identifier.uri | https://hdl.handle.net/20.500.12662/3230 | |
| dc.identifier.volume | 56 | en_US |
| dc.indekslendigikaynak | Scopus | en_US |
| dc.language.iso | en | en_US |
| dc.relation.ispartof | World Academy of Science, Engineering and Technology | en_US |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Classification | en_US |
| dc.subject | Decision tree | en_US |
| dc.subject | Entropy | en_US |
| dc.subject | Gini | en_US |
| dc.subject | Pruning | en_US |
| dc.subject | Split | en_US |
| dc.title | An attribute-centre based decision tree classification algorithm | en_US |
| dc.type | Article | en_US |
