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

Author

Listed:
  • 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.

Suggested Citation

  • Limin Wang & Xiaolin Li & Yuting Mao, 2008. "A Novel Approach of Multiple Submodel Integration Based on Decision Forest Construction," Modern Applied Science, Canadian Center of Science and Education, vol. 2(2), pages 1-9, March.
    • Handle: RePEc:ibn:masjnl:v:2:y:2008:i:2:p:9
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    Citations

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    Cited by:

    1. Yahya Parvizi & Manochehr Gorji & Mahmoud Omid & Mohammad Hossain Mahdian & Manochehr Amini, 2010. "Determination of Soil Organic Carbon Variability of Rainfed Crop Land in Semi-arid Region (Neural Network Approach)," Modern Applied Science, Canadian Center of Science and Education, vol. 4(7), pages 1-25, July.
    2. Y. Parvizi & M. Heshmati, 2015. "Detection of the effects of management and physical factors on forest soil carbon stock variability in semiarid conditions using parametric and nonparametric methods," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 61(10), pages 448-455.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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