<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">N. Benoudjit</style></author><author><style face="normal" font="default" size="100%">D. François</style></author><author><style face="normal" font="default" size="100%">M. Meurens</style></author><author><style face="normal" font="default" size="100%">M. Verleysen</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Spectrophotometric variable selection by mutual information</style></title><secondary-title><style face="normal" font="default" size="100%">Chemometrics and intelligent laboratory systems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.sciencedirect.com/science/article/pii/S0169743904001406</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">74</style></volume><pages><style face="normal" font="default" size="100%">243-251</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Spectrophotometric data often comprise a great number of numerical components or variables that can be used in&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/mathematics/calibration-model&quot; title=&quot;Learn more about Calibration Model from ScienceDirect's AI-generated Topic Pages&quot;&gt;calibration models&lt;/a&gt;. 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–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&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/chemistry/spectrophotometry&quot; title=&quot;Learn more about Spectrophotometry from ScienceDirect's AI-generated Topic Pages&quot;&gt;spectrophotometry&lt;/a&gt;&amp;nbsp;show the improvements obtained with respect to traditional and nonlinear calibration models.</style></abstract><issue><style face="normal" font="default" size="100%">02</style></issue></record></records></xml>