A Bayesian Feature Selection Method for Multiclass Classification with Application to Cancer Gene Expression Data
This paper proposes a Bayesian multiclass feature selection method using the relative belief ratio to identify discriminative genes in high-dimensional cancer datasets, demonstrating competitive classification accuracy and improved interpretability across various cancer types compared to existing filter-based approaches.