A novel prediction method for body fat by using choquet integral with respect to l-measure and gamma-support

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Title:	A novel prediction method for body fat by using choquet integral with respect to l-measure and gamma-support
Authors:	Chen, I-Ju;Lee, Ming-Jung;Jeng, Bai-Cheng;Wu, Der-Bang
Contributors:	Office of Physical Education
Keywords:	Biochemistry;Control theory;Cybernetics;Integral equations;Mathematical models;Robot learning;Body composition;Body fats;Choquet integral;Cross validation;L-measure;Multiple regression model;Prediction methods;Prediction model;Prediction schemes;Regression model;Ridge regression
Date:	2009
Issue Date:	2010-04-08 12:58:56 (UTC+0)
Publisher:	Asia University
Abstract:	Establishing a good algorithm for predicting body fat of body composition is an important issue. In this study, a novel body fat prediction method by using Choquet integral regression model based on L-measure and Gamma-support is proposed. For evaluating the performance of this new algorithm, a 5-fold Cross-Validation RMSE is performed. Experimental result shows that this new prediction scheme is better than the Choquet integral regression model based on Gamma-measure and P-measure, respectively and two traditional prediction models, ridge regression and multiple regression models, respectively. © 2009 IEEE.
Relation:	Proceedings of the 2009 International Conference on Machine Learning and Cybernetics 6 :3172-3176
Appears in Collections:	[體育室] 會議論文

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