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RESEARCH PRODUCT
Application of the modelling power approach to variable subset selection for GA-PLS QSAR models
Mark T. D. CroninSalvador Sagradosubject
Quantitative structure–activity relationshipChemistrybusiness.industryQuantitative Structure-Activity RelationshipFeature selectionFunction (mathematics)Machine learningcomputer.software_genreModels BiologicalBiochemistryPlot (graphics)Analytical ChemistryPower (physics)StatisticsPartial least squares regressionGenetic algorithmEnvironmental ChemistryArtificial intelligenceLeast-Squares AnalysisbusinesscomputerAlgorithmsSpectroscopySelection (genetic algorithm)description
A previously developed function, the Modelling Power Plot, has been applied to QSARs developed using partial least squares (PLS) following variable selection from a genetic algorithm (GA). Modelling power (Mp) integrates the predictive and descriptive capabilities of a QSAR. With regard to QSARs for narcotic toxic potency, Mp was able to guide the optimal selection of variables using a GA. The results emphasise the importance of Mp to assess the success of the variable selection and that techniques such as PLS are more robust following variable selection.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2007-09-07 | Analytica Chimica Acta |