ClassifyResult          Container for Storing Classification Results
CrossValParams          Parameters for Cross-validation Specification
FeatureSetCollection-class
                        Container for Storing A Collection of Sets
HuRI                    Human Reference Interactome
METABRICclinical        METABRIC Clinical Data
ModellingParams         Parameters for Data Modelling Specification
PredictParams           Parameters for Classifier Prediction
ROCplot                 Plot Receiver Operating Curve Graphs for
                        Classification Results
SelectParams            Parameters for Feature Selection
TrainParams             Parameters for Classifier Training
TransformParams         Parameters for Data Transformation
asthma                  Asthma RNA Abundance and Patient Classes
available               List Available Feature Selection and
                        Classification Approaches
calcCostsAndPerformance
                        Various Functions for Evaluating Precision
                        Pathways
calcExternalPerformance
                        Add Performance Calculations to a
                        ClassifyResult Object or Calculate for a Pair
                        of Factor Vectors
colCoxTests             A function to perform fast or standard Cox
                        proportional hazard model tests.
crissCrossPlot          A function to plot the output of the
                        crissCrossValidate function.
crissCrossValidate      A function to perform pairwise cross validation
crossValidate           Cross-validation to evaluate classification
                        performance.
distribution            Get Frequencies of Feature Selection or
                        Sample-wise Predictive Performance
edgesToHubNetworks      Convert a Two-column Matrix or Data Frame into
                        a Hub Node List
featureSetSummary       Transform a Table of Feature Abundances into a
                        Table of Feature Set Abundances.
interactorDifferences   Convert Individual Features into Differences
                        Between Binary Interactors Based on Known
                        Sub-networks
performancePlot         Plot Performance Measures for Various
                        Classifications
plotFeatureClasses      Plot Density, Scatterplot, Parallel Plot or Bar
                        Chart for Features By Class
precisionPathwaysTrain
                        Precision Pathways for Sample Prediction Based
                        on Prediction Confidence.
prepareData             Convert Different Data Classes into DataFrame
                        and Filter Features
rankingPlot             Plot Pair-wise Overlap of Ranked Features
runTest                 Perform a Single Classification
runTests                Reproducibly Run Various Kinds of
                        Cross-Validation
samplesMetricMap        Plot a Grid of Sample-wise Predictive Metrics
samplesSplits           Split Sample Indexes into Training and Test
                        Partitions for Cross-validation Taking Into
                        Account Classes.
selectionPlot           Plot Pair-wise Overlap, Variable Importance or
                        Selection Size Distribution of Selected
                        Features
