QSAR Modelling Using Genetic Algorithm Based Variable Selection

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Documentation for package ‘gaQSAR’ version 1.2.3

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

createBestFitnessPlot	Plot best fitness per generation
createDCVTrainingMetricsPlot	Plot training metrics (R2, R2adj, Q2) versus model size for nested CV runs
createDCVWilliamsPlot	Williams plot for double cross-validation diagnostics
createQ2Plot	Plot Q2 versus number of predictors
createWilliamsPlot	Create Williams plots for QSAR model diagnostics
gaDoubleCrossValidation	Nested (double) cross-validation for GA-based variable selection
gaintegerMutation	Integer-valued GA mutation operator
gaintegerOnePointCrossover	Integer-valued one-point crossover operator
gaintegerPopulation	Integer-valued GA population initializer
gaintegerTwoPointCrossover	Integer-valued two-point crossover operator
gaPermutationTest	Y-scrambling permutation test for GA-based variable selection
gaVariableSelection	Genetic algorithm based variable selection for QSAR
plot.gaQSAR	Plot method for gaQSAR objects
plot.gaQSAR_dcv	Plot method for gaQSAR_dcv objects
plot.gaQSAR_permTest	Plot method for gaQSAR_permTest objects
predictOOBObjects	Predict out-of-bag objects and compute external Q2
print.gaQSAR	Print method for gaQSAR objects
print.gaQSAR_dcv	Print method for gaQSAR_dcv objects
print.gaQSAR_permTest	Print method for gaQSAR_permTest objects
Q2	Compute Q2 (cross-validated R-squared)
QSARMonitorFactory	GA monitor function for QSAR variable selection
singleCV	LOOCV Q2 fitness function for small datasets
splitUp	Split data into training and test sets
summary.gaQSAR	Summary method for gaQSAR objects
summary.gaQSAR_dcv	Summary method for gaQSAR_dcv objects
summary.gaQSAR_permTest	Summary method for gaQSAR_permTest objects