In this paper, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define parallel discriminant hyperplanes for the ordinal ...
In this paper, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define parallel discriminant hyperplanes for the ordinal...
We present two new support vector approaches for ordinal regression. These approaches find the concentric spheres with minimum volume that contain most of the training samples. B...
Abstract. This paper studies a risk minimization approach to estimate a transformation model from noisy observations. It is argued that transformation models are a natural candidat...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
— Ordinal regression is an important type of learning, which has properties of both classification and regression. Here we describe an effective approach to adapt a traditional ...