Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0950-7051(99)00009-X
DC FieldValue
dc.titleOn mapping decision trees and neural networks
dc.contributor.authorSetiono, R.
dc.contributor.authorLeow, W.K.
dc.date.accessioned2013-07-15T05:25:36Z
dc.date.available2013-07-15T05:25:36Z
dc.date.issued1999
dc.identifier.citationSetiono, R., Leow, W.K. (1999). On mapping decision trees and neural networks. Knowledge-Based Systems 12 (3) : 95-99. ScholarBank@NUS Repository. https://doi.org/10.1016/S0950-7051(99)00009-X
dc.identifier.issn09507051
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/42909
dc.description.abstractThere exist several methods for transforming decision trees to neural networks. These methods typically construct the networks by directly mapping decision nodes or rules to the neural units. As a result, the networks constructed are often larger than necessary. This article describes a pruning-based method for mapping decision trees to neural networks, which can compress the network by removing unimportant and redundant units and connections. In addition, equivalent decision trees extracted from the pruned networks are simpler than those induced by well-known algorithms such as ID3 and C4.5.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/S0950-7051(99)00009-X
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentCOMPUTER SCIENCE
dc.contributor.departmentINFORMATION SYSTEMS
dc.description.doi10.1016/S0950-7051(99)00009-X
dc.description.sourcetitleKnowledge-Based Systems
dc.description.volume12
dc.description.issue3
dc.description.page95-99
dc.description.codenKNSYE
dc.identifier.isiut000081931600002
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