Model of information contribution of evaluation index system based on principal component- entropy

Abstract

Abstract: The establishment of evaluation index system in various evaluation researches is an important and indispensable research content. If the information content of the eventual evaluation index system has too much loss, any evaluation index system makes no sense. Combining principal component analysis method and information entropy method, this paper establishes the measurement model of the information contribution of eventual evaluation index system compared to the mass-election evaluation index system. In this paper,the main characteristics and innovations lie in the following aspects. First, it uses principal component analysis and information entropy to measure information contents of the index system, to establish the measuring model of information contributions of the evaluation index system compared to the mass-election index system, to change the existing studies which only consider the selection problem of the evaluation index and neglect the information contribution problem, and to solve the measuring problem of the information contributions. Second, the example shows that eventual evaluation index system retains 94.4% information content of mass-election evaluation index system.

Key words: evaluation index system, mass-selection index system, information contribution, principal component, entropy

CLC Number:

N945.16

Chi Guotai, Li Zhanjiang. Model of information contribution of evaluation index system based on principal component- entropy[J]. Science Research Management, 2014, 35(12): 137-144.

References

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