Information Sciences: an International Journal
Fuzzy regression analysis using neural networks
Fuzzy Sets and Systems
Properties of certain fuzzy linear regression methods
Fuzzy Sets and Systems
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
A generalized fuzzy weighted least-squares regression
Fuzzy Sets and Systems
Matrix computations (3rd ed.)
Fuzzy regression methods—a comparative assessment
Fuzzy Sets and Systems
Hybrid fuzzy least-squares regression analysis and its relibabilty measures
Fuzzy Sets and Systems
Fuzzy regression wiht radial basis function network
Fuzzy Sets and Systems
Proximal support vector machine classifiers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
A fuzzy linear regression model with better explanatory power
Fuzzy Sets and Systems - Information processing
Ridge Regression Learning Algorithm in Dual Variables
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
An "orderwise" polynomial regression procedure for fuzzy data
Fuzzy Sets and Systems
Computational Statistics & Data Analysis
Fuzzy nonparametric regression based on local linear smoothing technique
Information Sciences: an International Journal
Least squares estimation of a linear regression model with LR fuzzy response
Computational Statistics & Data Analysis
Information Sciences: an International Journal
Hi-index | 0.00 |
In this paper a new weighted fuzzy ridge regression method for a given set of crisp input and asymmetrical triangular fuzzy output values is proposed. In this approach the non-linear regression function is obtained by mapping the input samples into a higher dimensional feature space via a kernel function and constructing a linear regression estimation function in it. The method has the advantage that the solution is obtained by solving a system of linear equations. For the illustration of the proposed method a number of examples of importance are considered and the results obtained are compared with that of other methods. The results clearly demonstrate the effectiveness of our proposed method.