Deep Neural Networks for Rank-Consistent Ordinal Regression Based On Conditional Probabilities. (arXiv:2111.08851v4 [cs.LG] UPDATED)

In recent times, deep neural networks achieved outstanding predictive
performance on various classification and pattern recognition tasks. However,
many real-world prediction problems have ordinal response variables, and this
ordering information is ignored by conventional classification losses such as
the multi-category cross-entropy. Ordinal regression methods for deep neural
networks address this. One such method is the CORAL method, which is based on
an earlier binary label extension framework and achieves rank consistency among
its output layer tasks by imposing a weight-sharing …

arxiv consistent networks neural networks ordinal regression