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...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEE Transactions on fuzzy systems 13, 2 (2005).
1. Verfasser:	Dug Hun Hong
Format:	Artikel
Sprache:	English
Schlagworte:	Fuzzy regression analysis. High dimensional feature space. Interval regression analysis. Quadratic loss function. Quadratic programming. Support vector machine.