/SSHIBA_

Primary LanguageJupyter NotebookMIT LicenseMIT

SSHIBA

Here we present the algorithm Sparse Semi-supervised Heterogeneous Interbattery Bayessian Analysis along with the different modalities in which it can be used. In particular, we included 6 different notebooks to develop the functioning of the algorithm in different contexts, using different versions of the algorithm for each of them.

The main goal is to explain the usage of the method as well as showing some results with different databases.

The multilabel database has to be downloaded from a different link.