@article {14474,
	title = {Spectrophotometric variable selection by mutual information},
	journal = {Chemometrics and intelligent laboratory systems},
	volume = {74},
	number = {02},
	year = {2004},
	pages = {243-251},
	abstract = {Spectrophotometric data often comprise a great number of numerical components or variables that can be used in\&nbsp;calibration models. When a large number of such variables are incorporated into a particular model, many difficulties arise, and it is often necessary to reduce the number of spectral variables. This paper proposes an incremental (Forward{\textendash}Backward) procedure, initiated using an entropy-based criterion (mutual information), to choose the first variable. The advantages of the method are discussed; results in quantitative chemical analysis by\&nbsp;spectrophotometry\&nbsp;show the improvements obtained with respect to traditional and nonlinear calibration models.},
	url = {http://www.sciencedirect.com/science/article/pii/S0169743904001406},
	author = {N. Benoudjit and D. Fran{\c c}ois and M. Meurens and M. Verleysen}
}
