ParLeS: Software for chemometric analysis of spectroscopic data

被引:228
|
作者
Rossel, Raphael A. Viscarra [1 ]
机构
[1] Univ Sydney, Fac Agr Food & Nat Resources, Australian Ctr Precis Agr, Sydney, NSW 2006, Australia
关键词
spectroscopy; spectral preprocessing; principal components analysis; partial least squares regression; bootstrap aggregation; bagging-PLSR;
D O I
10.1016/j.chemolab.2007.06.006
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper describes the development and implementation of ParLeS, chemometrics software for multivariate modelling and prediction. ParLeS is shareware that was developed for teaching and research in chemometrics and spectroscopy; however, it may also be used with other types of multivariate data. ParLeS may be used to transform, preprocess and pretreat spectra using various algorithms; it may be used to implement principal components analysis (PCA); partial least squares regression (PLSR) with leave-n-out cross validation; and bootstrap aggregation-PLSR (bagging-PLSR). ParLeS facilitates the implementation of a large number of preprocessing techniques as well as bagging-PLSR, which can improve the robustness and accuracy of PLSR models. Other unique features of ParLeS include the provision of a number of assessment statistics and graphical output as well as a user-friendly interface and functionality. The implementation of ParLeS is demonstrated by modelling soil mid infrared (mid-IR) diffuse reflectance spectra for predictions of soil organic carbon. (c) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码:72 / 83
页数:12
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