Boosting model performance and interpretation by entangling preprocessing selection and variable selection

Analytica Chimica Acta

Volumn 938, Issue , 2016, Pages 44-52

  Gerretzen, Jan ^a,b   Szymańska, Ewa ^a,b   Bart, Jacob ^c   Davies, Antony N ^c,d   van Manen, Henk Jan ^c   van den Heuvel, Edwin R ^e   Jansen, Jeroen J ^a   Buydens, Lutgarde M C ^a  

^a RADBOUD UNIVERSITY NIJMEGEN   (Netherlands)

^b TI COAST ^*  (Netherlands)

^c AKZO NOBEL CENTRAL RESEARCH   (Netherlands)

^d UNIVERSITY OF GLAMORGAN   (United Kingdom)

^e EINDHOVEN UNIVERSITY OF TECHNOLOGY   (Netherlands)

Author keywords

Chemometrics; Design of experiments; Partial least squares; Preprocessing selection; Variable selection

Indexed keywords

LEAST SQUARES APPROXIMATIONS;

CHEMOMETRICS; PARTIAL LEAST SQUARE (PLS); PRE-PROCESSING METHOD; PREDICTIVE PERFORMANCE; PREPROCESSING SELECTION; SELECTION OF VARIABLES; VARIABLE SELECTION; VARIABLE SELECTION METHODS;

DESIGN OF EXPERIMENTS;

ARTICLE; CONTROLLED STUDY; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; MATHEMATICAL PHENOMENA; PREPROCESSING SELECTION; PRIORITY JOURNAL; PROCESS OPTIMIZATION; STATISTICAL ANALYSIS; SYSTEM ANALYSIS; VARIABLE SELECTION;

EID: 84995685030     PISSN: 00032670     EISSN: 18734324     Source Type: Journal    
DOI: 10.1016/j.aca.2016.08.022     Document Type: Article

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