Interval regression analysis using quadratic loss support vector machine.
Support vector machines (SVMs) have been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate interval linear and nonlinear regression models combining the possibility and necessity estimation formulation with the princi...
| Publié dans: | IEEE Transactions on fuzzy systems 13, 2 (2005). |
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| Auteur principal: | |
| Format: | Article |
| Langue: | English |
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