assessment-class        assessment: A central class to perform one and
                        two layers of external
classifyNewSamples-methods
                        classifyNewSamples Method to classify new
                        samples for a given
featureSelectionOptions-class
                        "featureSelectionOptions": A virtual class to
                        store the options of a
finalClassifier-class   finalClassifier: A class to store the final
                        classifier corresponding to
findFinalClassifier-methods
                        findFinalClassifier Method to train and build
                        the final classifier
geneSubsets-class       geneSubsets: A class to handle the sizes of
                        gene susbets to be tested
getDataset-methods      getDataset Method to access the attributes of a
                        dataset from an
getDataset<-            getDataset<- Method to modify the attributes of
                        a dataset from an
getFeatureSelectionOptions-methods
                        getFeatureSelectionOptions Method to access the
                        attributes of a
getFeatureSelectionOptions<-,assessment-method
                        getFeatureSelectionOptions<- Method to modify
                        the attributes of a
getFinalClassifier-methods
                        getFinalClassifier Method to access the
                        attributes of a finalClassifier
getResults-methods      getResults Method to access the result of
                        one-layer and two-layers
initialize,assessment-method
                        Initialize objects of class from Rmagpie
plotErrorsFoldTwoLayerCV-methods
                        plotErrorsFoldTwoLayerCV Method to plot the
                        error rate of a two-layer
plotErrorsRepeatedOneLayerCV-methods
                        plotErrorsRepeatedOneLayerCV Method to plot the
                        estimated error rates
plotErrorsSummaryOneLayerCV-methods
                        plotErrorsSummaryOneLayerCV Method to plot the
                        summary estimated error
rankedGenesImg-methods
                        rankedGenesImg Method to plot the genes
                        according to their frequency in
runOneLayerExtCV-methods
                        runOneLayerExtCV: Method to run an external
                        one-layer cross-validation
runTwoLayerExtCV-methods
                        runTwoLayerExtCV: Method to run an external
                        two-layers cross-validation
show,assessment-method
                        show Display the object, by printing, plotting
                        or whatever suits its
thresholds-class        thresholds: A class to handle the thresholds to
                        be tested during
vV70genes               vV70genes: van't Veer et al. 70 best genes in
                        an object of class
