| Literature DB >> 27477460 |
Lennart Eriksson1, Josefin Rosén2, Erik Johansson3, Johan Trygg4.
Abstract
Partial least squares (PLS) regression is a flexible data analytical approach, which can be made even more versatile and useful by various modifications. In this article we describe the extension into orthogonal PLS modeling, in terms of two new methods, called OPLS and O2PLS, with similar prediction capacity but improved model interpretation.Entities:
Keywords: Interpretability; Latent variables; Orthogonal variation; Predictive variation
Year: 2012 PMID： 27477460 DOI： 10.1002/minf.201200158
Source DB: PubMed Journal: Mol Inform ISSN： 1868-1743 Impact factor: 3.353