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

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Documentation for package ‘ClassifyR’ version 3.2.7

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

Help Pages

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
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
distribution	Get Frequencies of Feature Selection and Sample-wise Classification Errors
distribution-method	Get Frequencies of Feature Selection and Sample-wise Classification Errors
edgesToHubNetworks	Convert a Two-column Matrix or Data Frame into a Hub Node List
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
HuRI	Human Reference Interactome
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
length-method	Container for Storing A Collection of Sets
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
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
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
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
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
[-method	Container for Storing A Collection of Sets
[[-method	Container for Storing A Collection of Sets