aucMCV                  AUC multiple cross-validation
autoscale               Unit variance scaling method performed on the
                        columns of the data (i.e. metabolite
                        concentrations measured by 1H NMR or binned 1H
                        NMR spectra)
cachexiaData            Metabolite concentrations
combinatorialRFMCCV     Combinatorial Monte Carlo CV
forestPerformance       Characterizing the performance of a Random
                        Forest model
getAvgAUC               Computing the average AUC
getBestRFModel          Extracting the best performing Random Forest
                        model
lqvarFilter             Filtering 'low quality' variables from the
                        original dataset
mccv                    mccv class
mds                     mds class
meanCenter              Mean centering performed on the columns of the
                        data (i.e. metabolite concentrations measured
                        by 1H NMR or binned 1H NMR spectra)
optimizeMTRY            Mtry Optimization
paretoscale             Pareto scaling method performed on the columns
                        of the data table (i.e. metabolite
                        concentrations measured by 1H NMR or binned 1H
                        NMR spectra)
pca                     Principal Component Analysis
plot.mccv               Plotting single or multiple ROC curves of the
                        cross-validated Random Forest models
                        'plot.mccv' allows to plot single or multiple
                        ROC curves to characterize the performace of a
                        cross-validated Random Forest model
plot.mds                Multi-dimensional Scaling (MDS) Plot
plot.pca.loadings       PCA Loadings plot
plot.pca.scores         PCA Scores plot
plotAUCvsCombinations   Plotting the average AUC as a function of the
                        number of combinations
plotOOBvsMTRY           Plotting the average OOB error and its 95%
                        confidence interval as a function of the mtry
                        parameter
plotVarFreq             Variable Frequency Plot
rfMCCV                  Monte Carlo cross-validation of Random Forest
                        models
rfMCCVPerf              Extracting average accuracy and recall of a
                        list of Random Forest models
rsd                     Computing relative standard deviation of a
                        vector
rsdFilter               Filtering less informative variables
screeplot               Scree Plot
simpleData              simpleData
tuneMTRY                Tuning of the mtry parameter for a Random
                        Forest model
tuneNTREE               Tuning of the ntree parameter (i.e. the number
                        of trees) for a Random Forest model
