3 papers
stat.AP2026
A Bayesian Finite Mixture Model Approach for Mixed-type Data Clustering and Variable Selection with Censored Biomarkers
Yueting Wang, Shu Wang, Jonathan G. Yabes +1
Clustering mixed-type data remains a major challenge in biomedical research to uncover clinically meaningful subgroups within heterogeneous patient populations. Most existing clust…
stat.ML2019
A Bayesian Finite Mixture Model with Variable Selection for Data with Mixed-type Variables
Shu Wang, Jonathan G. Yabes, Chung-Chou H. Chang
Finite mixture model is an important branch of clustering methods and can be applied on data sets with mixed types of variables. However, challenges exist in its applications. Firs…
stat.ML2019
Hybrid Density- and Partition-based Clustering Algorithm for Data with Mixed-type Variables
Shu Wang, Jonathan G. Yabes, Chung-Chou H. Chang
Clustering is an essential technique for discovering patterns in data. The steady increase in amount and complexity of data over the years led to improvements and development of ne…