assessment-class        assessment: A central class to perform one and
                        two layers of external cross-validation on
                        microarray data
classifyNewSamples-methods
                        classifyNewSamples Method to classify new
                        samples for a given assessment
featureSelectionOptions-class
                        "featureSelectionOptions": A virtual class to
                        store the options of a feature selection
finalClassifier-class   finalClassifier: A class to store the final
                        classifier corresponding to an assessment
findFinalClassifier-methods
                        findFinalClassifier Method to train and build
                        the final classifier based on an assessment
geneSubsets-class       geneSubsets: A class to handle the sizes of
                        gene susbets to be tested during forward gene
                        selection
getDataset-methods      getDataset Method to access the attributes of a
                        dataset from an assessment
getDataset<-            getDataset<- Method to modify the attributes of
                        a dataset from an assessment
getFeatureSelectionOptions-methods
                        getFeatureSelectionOptions Method to access the
                        attributes of a featureSelectionOptions from an
                        assessment
getFeatureSelectionOptions<-,assessment-method
                        getFeatureSelectionOptions<- Method to modify
                        the attributes of a featureSelectionOptions
                        from an assessment
getFinalClassifier-methods
                        getFinalClassifier Method to access the
                        attributes of a finalClassifier from an
                        assessment
getResults-methods      getResults Method to access the result of
                        one-layer and two-layers cross-validation from
                        an assessment
initialize,assessment-method
                        Initialize objects of class from Rmagpie
plotErrorsFoldTwoLayerCV-methods
                        plotErrorsFoldTwoLayerCV Method to plot the
                        error rate of a two-layer Cross-validation
plotErrorsRepeatedOneLayerCV-methods
                        plotErrorsRepeatedOneLayerCV Method to plot the
                        estimated error rates in each repeat of a
                        one-layer Cross-validation
plotErrorsSummaryOneLayerCV-methods
                        plotErrorsSummaryOneLayerCV Method to plot the
                        summary estimated error rates of a one-layer
                        Cross-validation
rankedGenesImg-methods
                        rankedGenesImg Method to plot the genes
                        according to their frequency in a microarray
                        like image
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 class
thresholds-class        thresholds: A class to handle the thresholds to
                        be tested during training of the Nearest
                        Shrunken Centroid
vV70genes               vV70genes: van't Veer et al. 70 best genes in
                        an object of class dataset.
