Team, Visitors, External Collaborators
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
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Section: New Software and Platforms


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.