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.
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Donoso, S., Marín, N., Vila, M.A. (2007). Fuzzy Ridge Regression with Non Symmetric Membership Functions and Quadratic Models. In: Yin, H., Tino, P., Corchado, E., Byrne, W., Yao, X. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2007. IDEAL 2007. Lecture Notes in Computer Science, vol 4881. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77226-2_15
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DOI: https://doi.org/10.1007/978-3-540-77226-2_15
Publisher Name: Springer, Berlin, Heidelberg
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