کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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1181652 | 962969 | 2008 | 12 صفحه PDF | دانلود رایگان |
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.
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 90, Issue 1, 15 January 2008, Pages 72–83