Fuzzy ridge regression with non symmetric membership functions and quadratic models

Authors:
S. Donoso;N. Marín;M. A. Vila
Affiliations:
IDBIS Research Group, Dept. of Computer Science and A. I., E.T.S.I.I., University of Granada, Granada, Spain;IDBIS Research Group, Dept. of Computer Science and A. I., E.T.S.I.I., University of Granada, Granada, Spain;IDBIS Research Group, Dept. of Computer Science and A. I., E.T.S.I.I., University of Granada, Granada, Spain
Venue:
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Year:
2007

Citing 7
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Abstract

Fuzzy regression models has been traditionally considered as a problem of linear programming. The use of quadratic programming allows to overcome the limitations of linear programming as well as to obtain highly adaptable regression approaches. However, we verify the existence of multicollinearity in fuzzy regression and we propose a model based on Ridge regression in order to address this problem.