Ordinal Regression via Binary Preference vs Simple Regression: Statistical and Experimental Perspectives. (arXiv:2207.02454v1 [cs.LG])

Ordinal regression with anchored reference samples (ORARS) has been proposed
for predicting the subjective Mean Opinion Score (MOS) of input stimuli
automatically. The ORARS addresses the MOS prediction problem by pairing a test
sample with each of the pre-scored anchored reference samples. A trained binary
classifier is then used to predict which sample, test or anchor, is better
statistically. Posteriors of the binary preference decision are then used to
predict the MOS of the test sample. In this paper, rigorous …

arxiv binary experimental lg ordinal perspectives regression statistical