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| - Genetic Algorithm Guided Selection: Variable Selection and Subset Selection
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| - A novel Genetic Algorithm guided Selection method, GAS, has been described. The method utilizes a simpleencoding scheme which can represent both compounds and variables used to construct a QSAR/QSPR model.A genetic algorithm is then utilized to simultaneously optimize the encoded variables that include bothdescriptors and compound subsets. The GAS method generates multiple models each applying to a subsetof the compounds. Typically the subsets represent clusters with different chemotypes. Also a procedurebased on molecular similarity is presented to determine which model should be applied to a given test setcompound. The variable selection method implemented in GAS has been tested and compared using theSelwood data set (n = 31 compounds; v = 53 descriptors). The results showed that the method is comparableto other published methods. The subset selection method implemented in GAS has been first tested usingan artificial data set (n = 100 points; v = 1 descriptor) to examine its ability to subset data points andsecond applied to analyze the XLOGP data set (n = 1831 compounds; v = 126 descriptors). The methodis able to correctly identify artificial data points belonging to various subsets. The analysis of the XLOGPdata set shows that the subset selection method can be useful in improving a QSAR/QSPR model when thevariable selection method fails.
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