Europe PMC

L1 penalized continuation ratio models for ordinal response prediction using high-dimensional datasets.

Health status and outcomes are frequently measured on an ordinal scale. For high-throughput genomic datasets, the common approach to analyzing ordinal response data has been to break the problem into ...
IEEE

Hierarchical Bayesian variable selection in the probit model with mixture of nominal and ordinal responses

Abstract: Multi-class classification problems have been studied for pure nominal and pure ordinal responses. However, there are some cases where the multi-class responses are a mixture of nominal and ...
IEEE

Causation-Based Monitoring and Diagnosis for Multivariate Categorical Processes With Ordinal Information

Abstract: The monitoring and diagnosis of multivariate categorical processes (MCPs) have drawn increasing attention lately, as categorical variables have been frequently involved in modern quality ...