A Novel Approach of Multiple Submodel Integration Based on Decision Forest Construction

Limin Wang, Xiaolin Li, Yuting Mao

Abstract


An analytical general solution is derived for reasoning uncertain knowledge by multiple sub-model integration. By choosing decision rule for each specific instance, a decision forest rather than a tree will be constructed, thus all relatively independent attribute sets can be determined automatically without any human intervention. Necessary discretization for mixed-mode subset will be processed based on post-discretization strategy to minimize information loss.


Full Text: PDF DOI: 10.5539/mas.v2n2p9

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This work is licensed under a Creative Commons Attribution 3.0 License.

Modern Applied Science   ISSN 1913-1844 (Print)   ISSN 1913-1852 (Online)

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