Power-transformed-measure and its Choquet integral regression model

  • Authors:

  • Hsiang-Chuan Liu;Chin-Chun Chen;Guey-Shya Chen;Yu-Du Jheng

  • Affiliations:

  • Department of Bioinformatics, Asia University, Wufeng, Taichung County, Taiwan;Department of General Education, Min-Hwei College, Tainan, Taiwan;Graduate Institute of Educational Measurement, Taichung University, Taichung, Taiwan;Graduate Institute of Educational Measurement, Taichung University, Taichung, Taiwan

  • Venue:
  • ACS'07 Proceedings of the 7th Conference on 7th WSEAS International Conference on Applied Computer Science - Volume 7
  • Year:
  • 2007

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Abstract

Both the well known fuzzy measures, λ-measure and P-measure, have only one solution of measure function with no more choice. In this study, we propose the power-transformed-measures for any given fuzzy measure, those new measures with infinitely many solution of measure function can be chosen the best one to apply for improving the forecasting performances. A real data experiment by using a 5-fold cross-validation mean square error (MSE) is conducted. The performances of four Choquet integral regression models based onλ-measure, P-measure, power-transformed-measures of λ-measure, and power-transformed-measures of P-measure, respectively, ridge regression model, and the traditional multiple linear regression model are compared. Experimental results show that the performances of Choquet integral regression model based on the proposed power-transformed-measures outperform the performances of other models.