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Advanced PLS Techniques in Chemometrics and Their Applications to Molecular Design

Advanced PLS Techniques in Chemometrics and Their Applications to Molecular Design

Kiyoshi Hasegawa, Kimito Funatsu
Copyright: © 2011 |Pages: 24
ISBN13: 9781615209118|ISBN10: 1615209115|ISBN13 Softcover: 9781616923686|EISBN13: 9781615209125
DOI: 10.4018/978-1-61520-911-8.ch008
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MLA

Hasegawa, Kiyoshi, and Kimito Funatsu. "Advanced PLS Techniques in Chemometrics and Their Applications to Molecular Design." Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques, edited by Huma Lodhi and Yoshihiro Yamanishi, IGI Global, 2011, pp. 145-168. https://doi.org/10.4018/978-1-61520-911-8.ch008

APA

Hasegawa, K. & Funatsu, K. (2011). Advanced PLS Techniques in Chemometrics and Their Applications to Molecular Design. In H. Lodhi & Y. Yamanishi (Eds.), Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques (pp. 145-168). IGI Global. https://doi.org/10.4018/978-1-61520-911-8.ch008

Chicago

Hasegawa, Kiyoshi, and Kimito Funatsu. "Advanced PLS Techniques in Chemometrics and Their Applications to Molecular Design." In Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques, edited by Huma Lodhi and Yoshihiro Yamanishi, 145-168. Hershey, PA: IGI Global, 2011. https://doi.org/10.4018/978-1-61520-911-8.ch008

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Abstract

In quantitative structure-activity/property relationships (QSAR and QSPR), multivariate statistical methods are commonly used for analysis. Partial least squares (PLS) is of particular interest because it can analyze data with strongly collinear, noisy and numerous X variables, and also simultaneously model several response variables Y. Furthermore, PLS can provide us several prediction regions and diagnostic plots as statistical measures. PLS has evolved or changed for copying with sever demands from complex data X and Y structure. In this review article, the authors picked up four advanced PLS techniques and outlined their algorithms with representative examples. Especially, the authors made efforts to describe how to disclose the embedded inner relations in data and how to use their information for molecular design.

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