THOR: Threshold-Based Ranking Loss for Ordinal Regression. (arXiv:2205.04864v1 [cs.LG])

Web: http://arxiv.org/abs/2205.04864

In this work, we present a regression-based ordinal regression algorithm for
supervised classification of instances into ordinal categories. In contrast to
previous methods, in this work the decision boundaries between categories are
predefined, and the algorithm learns to project the input examples onto their
appropriate scores according to these predefined boundaries. This is achieved
by adding a novel threshold-based pairwise loss function that aims at
minimizing the regression error, which in turn minimizes the Mean Absolute
Error (MAE) measure. We …

arxiv loss ordinal ranking regression