Cross-validation for the selection of spectral variables using the successive projections algorithm

Abstract

Este trabalho compara o uso de um conjunto de validação separado e de validação cruzada amostra-a-amostra para guiar a seleção de variáveis no Algoritmo das Projeções Sucessivas (APS) para calibração multivariada. Análises de diesel e milho por espectrometria NIR são apresentadas. Uma interface gráfica do APS encontra-se disponível em www.ele.ita.br/ kawakami/spa/ This work compares the use of a separate validation set and leave-one-out cross-validation to guide the selection of variables in the Successive Projections Algorithm (SPA) for multivariate calibration. Two case studies involving diesel and corn analysis by NIR spectrometry are presented. A graphical interface for SPA is available at www.ele.ita.br/~kawakami/spa/

NIR spectrometric determination of quality parameters in vegetable oils using iPLS and variable selection

“…The predicted valuê y cal;n is obtained by removing the nth sample from the calibration set, building a model with the remaining ones, and applying this model to the removed sample. The selection of individual wavenumbers within the spectral interval obtained by iPLS was carried out by using a lab-made SPA routine implemented in Matlab Ò 6.5, as described elsewhere (Galvão, 2007;Galvão & Araú jo, 2008;Galvão et al, 2007). The selection process is guided by the RMSECV metric defined in Eq.…”

Multivariate Modeling in Quality Control of Viscosity in Fuel: An Application in Oil Industry

“…12. Representation of online determination of viscosity by mathematical modeling (adapted from Early Jr, 1990) The preprocessing that provided the best result was the first derivative of the second-degree polynomial proposed by Savitzky-Golay (Galvão et al, 2007), that highlight the differences between samples, contributing to the model can be used to explain the variance between them. The Fig.…”

An imaging dataset of cervical cells using scanning near-field optical microscopy coupled to an infrared free electron laser

“…SPA is a variable selection technique specifically designed to improve the conditioning of multiple linear regression by minimizing collinearity effects in the calibration data set and can result in models with good prediction ability 24 .…”