.png){kind=icon}
.png){kind=icon}
Return
The successive projections algorithm
.png){kind=icon}
PRE
AI
DOI：10.1016/j.trac.2012.09.006.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
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.
Keywords:
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
Journal
IF:
12
Papers:
7.3K
Citations:
3.9W