Support Vector Ordinal Regression using Privileged Information

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 regres- sion. The privileged information is incorporated during the training by modelling the slacks through correcting functions for each of the paral- lel 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 perfor- mance significantly.