返回
The successive projections algorithm
DOI:10.1016/j.trac.2012.09.006.png)
摘要
En 中文
The successive projections algorithm (SPA) is a variable-selection technique that has attracted increasing interest in the analytical-chemistry community in the past 10 years. The present review presents the basic features of SPA for Multiple Linear Regression (MLR) and Linear Discriminant Analysis (LDA) and reports some variants that have been proposed for sample selection, calibration transfer and Quantitative Structure-Activity Relationship (QSAR) and Quantitative Structure-Property Relationship (QSPR) studies. We also discuss computational and pre-processing issues. By way of illustration we present two case studies involving near-infrared determination of protein in wheat and voltammetric classification of vegetable oils. The code employed in this article is freely available from us upon request. (c) 2012 Elsevier Ltd. All rights reserved.
Keyword:
Calibration transfer
Classification
Linear Discriminant Analysis (LDA)
Multiple Linear Regression (MLR)
Multivariate calibration
Quantitative Structure-Activity Relationship (QSAR)
Quantitative Structure-Property Relationship (QSPR)
Sample selection
Successive projections algorithm (SPA)
Variable selection
期刊
IF:
12
论文数:
7.3K
被引数:
3.9W
机构
引用论文
Near infrared reflectance spectrometry classification of cigarettes using the successive projections algorithm for variable selection使用连续投影算法进行变量选择的卷烟近红外反射光谱分类
TALANTA
IF6.1
UV-Vis spectrometric classification of coffees by SPA-LDA通过spa-lda对咖啡进行uv-vis光谱分类
FOOD CHEMISTRY
IF9.8
Simultaneous determination of hydroquinone, resorcinol, phenol, m-cresol and p-cresol in untreated air samples using spectrofluorimetry and a custom multiple linear regression-successive projection algorithm
TALANTA
IF6.1
Flow-batch technique for the simultaneous enzymatic determination of levodopa and carbidopa in pharmaceuticals using PLS and successive projections algorithm
TALANTA
IF6.1

