A new validation criterion for guiding the selection of variables by the successive projections algorithm in classification problems

Abstract

A simplification in SPA-LDA is proposed to circumvent the need for separate training and validation sets. The number of degrees of freedom is employed in the cost function to avoid model overfitting. Three examples are presented: classification of coffee, diesel and vegetable oils by using UV-Vis spectrometry, NIR spectrometry and voltammetry, respectively.

variable selection; successive projections algorithm; classification; model validation