Algorithm of Model Selection in Decision Support System

Feng, Yanghe; Dai, Chaofan; Deng, Su

doi:10.1109/itcs.2009.203

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2011

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“…The structure of the model can be represented by knowledge framework, then the reasoning trees are established according to the fact base and the knowledge base. Thus a knowledge-based automatic model selection method is proposed by integrating the experience and expert knowledge [2][3][4] . Gradient-based approaches are developed for model selection and present impressive gain in time complexity [5][6] , but they may fall into bad local minima.…”

Section: Introductionmentioning

confidence: 99%

Evolutioinary Combination of models in DSS based on Genetic Programming

Dai¹,

Feng²,

Shi³

2011

JSW

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The efficiency of model-aided decision making relies on the intelligent level of model selection. The purpose of this paper is to develop a new algorithm for model selection based on genetic programming. In the algorithm, the meta-models are classified according to the characteristics of the sample data, and the combined models are built as tree format. The genetic operations are performed under some constraints to produce combination models for users’ reference. The process of the algorithm greatly decreases users’ dependence on domain knowledge.