Using ensemble and learning techniques towards extending the knowledge Discovery Pipeline.

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dc.contributor.authorYu, N Cheah
dc.date.accessioned2017-09-14T04:18:21Z
dc.date.available2017-09-14T04:18:21Z
dc.date.issued2002
dc.description.abstractThe generation of a huge amount of data by an enterprise is of great concern to decision makers. This problem is compounded by the many environmental challenges that an enterprise faces in the effort to produce better products and services. It is highly crucial to know what goes on in its business transactions both internally and externally and to examine the heart of an enterprise's transactions, that is its data, and to transform it into actionable knowledge through the process of knowledge discovery.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/4641
dc.subjectKnowledge discoveryen_US
dc.subjectClustering ensembleen_US
dc.subjectNeural network ensembleen_US
dc.subjectDiscretizationen_US
dc.subjectRough set analysisen_US
dc.titleUsing ensemble and learning techniques towards extending the knowledge Discovery Pipeline.en_US
dc.typeWorking Paperen_US
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