Support Vector Ordinal Regression using Privileged Information
Fengzhen Tang, Peter Tiňo, Pedro Antonio Gutiérrez, Huanhuan Chen · 2014
Abstract. We introduce a new methodology, called SVORIM+, for utilizing privileged information of the training examples, unavailable in the test regime, to improve generalization performance in ordinal regression. The privileged information is incorporated during the training by modelling the slacks through correcting functions for each of the parallel hyperplanes separating the ordered classes. The experimental results on several benchmark and time series datasets show that inclusion of the privileged information during training can boost the generalization performance significantly. 1