Multiblock chemometrics for the discrimination of three extra virgin olive oil varieties.
Sign Up to like & getrecommendations! Published in 2019 at "Food chemistry"
DOI: 10.1016/j.foodchem.2019.125588
Abstract: To discriminate samples from three varieties of Tunisian extra virgin olive oils, weighted and non-weighted multiblock partial least squares - discriminant analysis (MB-PLS1-DA) models were compared to PLS1-DA models using data obtained by gas chromatography… read more here.
Keywords: extra virgin; pls1; pls1 models; virgin olive ... See more keywords
Improved multi-class discrimination by Common-Subset-of-Independent-Variables Partial-Least-Squares Discriminant Analysis.
Sign Up to like & getrecommendations! Published in 2021 at "Talanta"
DOI: 10.1016/j.talanta.2021.122595
Abstract: In this study, a new PLS-DA modelling approach for multi-class discriminant analysis, called Common-Subset-of-Independent-Variables Partial-Least-Squares Discriminant Analysis is proposed and evaluated. Because in this method Partial-Least-Squares models for one component are used, it is denoted… read more here.
Keywords: csiv pls1; multi class; discriminant analysis; pls1 ... See more keywords
Improved modelling for low-correlated multiple responses by common-subset-of-independent-variables partial-least-squares.
Sign Up to like & getrecommendations! Published in 2021 at "Talanta"
DOI: 10.1016/j.talanta.2021.123140
Abstract: In this study, a new approach for PLS modelling for low-correlated multiple responses, called Common-Subset-of-Independent-Variables Partial-Least-Squares, denoted as CSIV-PLS1, is proposed and evaluated. In CSIV-PLS1, for each response vector, individual PLS1 models with individual model… read more here.
Keywords: multiple responses; method; pls1; correlated multiple ... See more keywords