A Novel Approach of Multiple Submodel Integration Based on Decision Forest Construction
Limin Wang, Xiaolin Li, Yuting Mao · Modern Applied Science · 2008
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.