mvlearnR and Shiny App for multiview learning

1 code implementation • 25 Nov 2023 • Elise F. Palzer, Sandra E. Safo

For users with limited programming language, we provide a Shiny Application to facilitate data integration anywhere and on any device.

Data Integration Multiview Learning

sJIVE: Supervised Joint and Individual Variation Explained

1 code implementation • 26 Feb 2021 • Elise F. Palzer, Christine Wendt, Russell Bowler, Craig P. Hersh, Sandra E. Safo, Eric F. Lock

We propose a method called supervised joint and individual variation explained (sJIVE) that can simultaneously (1) identify shared (joint) and source-specific (individual) underlying structure and (2) build a linear prediction model for an outcome using these structures.