VICatMix: variational Bayesian clustering and variable selection for discrete biomedical data
VICatMix:面向离散生物医学数据的变分贝叶斯聚类与变量选择
Effective clustering of biomedical data is crucial in precision medicine, enabling accurate stratifiction of patients or samples. However, the growth in availability of high-dimensional categorical data, including `omics data, necessitates computationally efficient clustering algorithms. We present VICatMix, a variational Bayesian finite mixture model designed for the clustering of categorical data. The use of variational inference (VI) in its training allows the model to…