Hierarchical sparse Bayesian multitask learning for disease prediction in pooled microbiome studies
A hierarchical Bayesian multitask learning model that is applicable to the general multi-task binary classification learning problem where the model assumes a shared sparsity structure across different tasks is proposed and derived based on variational inference to approximate the posterior distribution.
Hao-Nan Zhu, Andre R. Goncalves, Car Reen Kok et al.
· BioData Mining · 1 citation