Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/73189
Type: Artigo de periódico
Title: Variable selection in QSAR.
Author: Ferreira, MMC
Montanari, CA
Gaudio, AC
Abstract: VARIABLE SELECTION IN QSAR, The process of building mathematical models in quantitative structure-activity relationship (QSAR) studies is generally limited by the size of the dataset used to select variables from. For huge datasets, the task of selecting a given number of variables that produces the best linear model can be enormous, if not unfeasible, In this case, some methods can be used to separate good parameter combinations from the bad ones. In this paper three methodologies are analyzed: systematic search, genetic algorithm and chemometric methods. These methods have been exposed and discussed through practical examples.
Subject: systematic search
genetic algorithm
chemometric methods
Country: Brasil
Editor: Soc Brasileira Quimica
Rights: aberto
Identifier DOI: 10.1590/S0100-40422002000300017
Date Issue: 2002
Appears in Collections:Unicamp - Artigos e Outros Documentos

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