Support vector machines in fuzzy regression
Paulina Wieszczy , Przemysław Grzegorzewski
This paper presents methods of estimating fuzzy regression models based on support vector machines. Starting from the approaches known from the literature and dedicated to triangular fuzzy numbers and based on linear and quadratic loss, a new method applying loss function based on the Trutschnig distance is proposed. Furthermore, a generalization of those models for fuzzy numbers with trapezoidal membership function is given. Finally, the proposed models are illustrated and compared in the examples and some of their properties are discussed.
|Book||Studies in Computational Intelligence, Studies in Computational Intelligence, 2016, ISBN 9783319301648, 103-138 p.|
|Score||= 0.0, 06-12-2019, MonographChapterAuthor|
|Publication indicators||= 0; = 0; : 2016 = 0.39|
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