Section: New Software and Platforms

dd-sPLS

Data-Driven Sparse PLS

Keywords: Marker selection - Classification - Regression - Missing data - Multi-Block - High Dimensional Data - PLS - SVD

Scientific Description: Allows to build Multi-Data-Driven Sparse PLS models. Multi-blocks with high-dimensional settings are particularly sensible to this. Whatsmore it deals with missing samples (entire lines missing per block) thanks to the Koh-Lanta algorithm. SVD decompositions permit to offer a fast and controlled method.

Functional Description: That software solves the missing samples problem selecting interesting variables under multi-block supervised settings.

• Contact: Hadrien Lorenzo

• URL: https://hadrienlorenzo.netlify.com/projects/ddspls/