Articolo in rivista, 2012, ENG

Multivariate Additive PLS Spline Boosting in Agro-Chemistry Studies.

Lombardo R., Durand J.F., Leone A.P.

Lombardo R. (Unina2); Durand J.F. (Montpellier University, France)

Routinely, the multi-response Partial Least-Squares (PLS) is used in regression and classification problems showing good performances in many applied studies. In this paper, we aim to present PLS via spline functions focusing on supervised classification studies and showing how PLS methods historically belong to L2 boosting family. The theory of the PLS boost models is presented and used in classification studies. As a natural enrichment of linear PLS boost, we present its multi-response non-linear version by univariate and bivariate spline functions to transform the predictors. Three case studies of different complexities concerning soils and its products will be discussed, showing the gain in diagnostic provided by the non-linear additive PLS boost discriminant analysis compared to the linear one.

Current analytical chemistry (Print) 8 (2), pp. 236–253

Keywords

PLS regression, L2 boost, B-splines, Discriminant Analysis, Generalized Cross-Validation

CNR authors

Leone Antonio Pasquale

CNR institutes

ISAFoM – Istituto per i sistemi agricoli e forestali del mediterraneo

ID: 51883

Year: 2012

Type: Articolo in rivista

Creation: 2012-01-23 00:00:00.000

Last update: 2015-02-06 20:04:47.000

External links

OAI-PMH: Dublin Core

OAI-PMH: Mods

OAI-PMH: RDF

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:51883

ISI Web of Science (WOS): 000303474200006