# A framework for cross-validated classification problems, with applications to differential variability and differential distribution testing

## Documentation for package ‘ClassifyR’ version 3.2.0

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

## Help Pages

A C D E F G H I L M P R S T misc

## -- A --

actualOutcome | Container for Storing Classification Results
actualOutcome-method | Container for Storing Classification Results
allFeatureNames | Container for Storing Classification Results
allFeatureNames-method | Container for Storing Classification Results
asthma | Asthma RNA Abundance and Patient Classes
available | List Available Feature Selection and Classification Approaches

## -- C --

calcCVperformance | Add Performance Calculations to a ClassifyResult Object or Calculate for a Pair of Factor Vectors
calcCVperformance-method | Add Performance Calculations to a ClassifyResult Object or Calculate for a Pair of Factor Vectors
calcExternalPerformance | Add Performance Calculations to a ClassifyResult Object or Calculate for a Pair of Factor Vectors
calcExternalPerformance-method | Add Performance Calculations to a ClassifyResult Object or Calculate for a Pair of Factor Vectors
calcPerformance | Add Performance Calculations to a ClassifyResult Object or Calculate for a Pair of Factor Vectors
chosenFeatureNames | Container for Storing Classification Results
chosenFeatureNames-method | Container for Storing Classification Results
classes | Asthma RNA Abundance and Patient Classes
ClassifyResult | Container for Storing Classification Results
ClassifyResult-class | Container for Storing Classification Results
ClassifyResult-method | Container for Storing Classification Results
colCoxTests | A function to perform fast or standard Cox proportional hazard model tests.
crossValidate | Cross-validation to evaluate classification performance.
crossValidate,MultiAssayExperiment-method, | Cross-validation to evaluate classification performance.
crossValidate-method | Cross-validation to evaluate classification performance.
CrossValParams | Parameters for Cross-validation Specification
CrossValParams-class | Parameters for Cross-validation Specification

## -- D --

distribution | Get Frequencies of Feature Selection and Sample-wise Classification Errors
distribution-method | Get Frequencies of Feature Selection and Sample-wise Classification Errors

## -- E --

edgesToHubNetworks | Convert a Two-column Matrix or Data Frame into a Hub Node List

## -- F --

features | Container for Storing Classification Results
features-method | Container for Storing Classification Results
FeatureSetCollection | Container for Storing A Collection of Sets
FeatureSetCollection-class | Container for Storing A Collection of Sets
FeatureSetCollection-method | Container for Storing A Collection of Sets
featureSetSummary | Transform a Table of Feature Abundances into a Table of Feature Set Abundances.
featureSetSummary-method | Transform a Table of Feature Abundances into a Table of Feature Set Abundances.
finalModel | Container for Storing Classification Results
finalModel-method | Container for Storing Classification Results

## -- G --

generateCrossValParams | A function to generate a CrossValParams object
generateModellingParams | A function to generate a ModellingParams object

## -- H --

HuRI | Human Reference Interactome

## -- I --

interactorDifferences | Convert Individual Features into Differences Between Binary Interactors Based on Known Sub-networks
interactorDifferences-method | Convert Individual Features into Differences Between Binary Interactors Based on Known Sub-networks
interactors | Human Reference Interactome

## -- L --

length-method | Container for Storing A Collection of Sets

## -- M --

measurements | Asthma RNA Abundance and Patient Classes
ModellingParams | Parameters for Data Modelling Specification
ModellingParams-class | Parameters for Data Modelling Specification
models | Container for Storing Classification Results
models-method | Container for Storing Classification Results

## -- P --

performance | Container for Storing Classification Results
performance-method | Container for Storing Classification Results
performancePlot | Plot Performance Measures for Various Classifications
performancePlot-method | Plot Performance Measures for Various Classifications
plotFeatureClasses | Plot Density, Scatterplot, Parallel Plot or Bar Chart for Features By Class
plotFeatureClasses-method | Plot Density, Scatterplot, Parallel Plot or Bar Chart for Features By Class
predict.trainedByClassifyR | Cross-validation to evaluate classification performance.
predictions | Container for Storing Classification Results
predictions-method | Container for Storing Classification Results
PredictParams | Parameters for Classifier Prediction
PredictParams-class | Parameters for Classifier Prediction
PredictParams-method | Parameters for Classifier Prediction
prepareData | Convert Different Data Classes into DataFrame and Filter Features
prepareData-method | Convert Different Data Classes into DataFrame and Filter Features

## -- R --

rankingPlot | Plot Pair-wise Overlap of Ranked Features
rankingPlot-method | Plot Pair-wise Overlap of Ranked Features
ROCplot | Plot Receiver Operating Curve Graphs for Classification Results
ROCplot-method | Plot Receiver Operating Curve Graphs for Classification Results
runTest | Perform a Single Classification
runTest-method | Perform a Single Classification
runTests | Reproducibly Run Various Kinds of Cross-Validation
runTests-method | Reproducibly Run Various Kinds of Cross-Validation

## -- S --

sampleNames | Container for Storing Classification Results
sampleNames-method | Container for Storing Classification Results
samplesMetricMap | Plot a Grid of Sample Error Rates or Accuracies
samplesMetricMap-method | Plot a Grid of Sample Error Rates or Accuracies
selectionPlot | Plot Pair-wise Overlap, Variable Importance or Selection Size Distribution of Selected Features
selectionPlot-method | Plot Pair-wise Overlap, Variable Importance or Selection Size Distribution of Selected Features
SelectParams | Parameters for Feature Selection
SelectParams-class | Parameters for Feature Selection
SelectParams-method | Parameters for Feature Selection
show-method | Container for Storing Classification Results
show-method | Container for Storing A Collection of Sets
show-method | Parameters for Classifier Prediction
show-method | Parameters for Feature Selection
show-method | Parameters for Classifier Training
show-method | Parameters for Data Transformation

## -- T --

totalPredictions | Container for Storing Classification Results
totalPredictions-method | Container for Storing Classification Results
train.data.frame | Cross-validation to evaluate classification performance.
train.DataFrame | Cross-validation to evaluate classification performance.
train.list | Cross-validation to evaluate classification performance.
train.matrix | Cross-validation to evaluate classification performance.
train.MultiAssayExperiment | Cross-validation to evaluate classification performance.
TrainParams | Parameters for Classifier Training
TrainParams-class | Parameters for Classifier Training
TrainParams-method | Parameters for Classifier Training
TransformParams | Parameters for Data Transformation
TransformParams-class | Parameters for Data Transformation
TransformParams-method | Parameters for Data Transformation
tunedParameters | Container for Storing Classification Results
tunedParameters-method | Container for Storing Classification Results

## -- misc --

[-method | Container for Storing A Collection of Sets
[[-method | Container for Storing A Collection of Sets