# A framework for two-class classification problems, with applications to differential variability and differential distribution testing.

## Documentation for package ‘ClassifyR’ version 1.0.18

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

## Help Pages

actualClasses | Container for Storing Classification Results
actualClasses-method | Container for Storing Classification Results
calcPerformance | Add Performance Calculations to a ClassifyResult object
calcPerformance-method | Add Performance Calculations to a ClassifyResult object
classifyInterface | Interface for PoiClaClu Package's Classify Function
ClassifyResult | Container for Storing Classification Results
ClassifyResult-class | Container for Storing Classification Results
ClassifyResult-method | Container for Storing Classification Results
distribution | Get Frequencies of Feature Selection and Sample Errors
distribution-method | Get Frequencies of Feature Selection and Sample Errors
DMDselection | Selection of Differential Distributions with Kullback Leibler Distance
DMDselection-method | Selection of Differential Distributions with Kullback Leibler Distance
edgeRselection | Feature Selection Based on Differential Expression for RNA-seq
edgeRselection-method | Feature Selection Based on Differential Expression for RNA-seq
errorMap | Plot a Grid of Sample Error Rates
errorMap-method | Plot a Grid of Sample Error Rates
features | Container for Storing Classification Results
features-method | Container for Storing Classification Results
fisherDiscriminant | Classification Using Fisher's LDA
fisherDiscriminant-method | Classification Using Fisher's LDA
functionOrList | Union of Functions and List of Functions
functionOrList-class | Union of Functions and List of Functions
getLocationsAndScales | Calculate Location and Scale
getLocationsAndScales-method | Calculate Location and Scale
KolmogorovSmirnovSelection | Selection of Differential Distributions with Kolmogorov Smirnov Distance
KolmogorovSmirnovSelection-method | Selection of Differential Distributions with Kolmogorov Smirnov Distance
KullbackLeiblerSelection | Selection of Differential Distributions with Kullback Leibler Distance
KullbackLeiblerSelection-method | Selection of Differential Distributions with Kullback Leibler Distance
leveneSelection | Selection of Differential Variability with Levene Statistic
leveneSelection-method | Selection of Differential Variability with Levene Statistic
likelihoodRatioSelection | Selection of Differential Distributions with Likelihood Ratio Statistic
likelihoodRatioSelection-method | Selection of Differential Distributions with Likelihood Ratio Statistic
limmaSelection | Selection of Differentially Expressed Features
limmaSelection-method | Selection of Differentially Expressed Features
mixmodels | Selection of Differential Distributions with Mixtures of Normals
mixModelsTest | Selection of Differential Distributions with Mixtures of Normals
mixModelsTest-method | Selection of Differential Distributions with Mixtures of Normals
mixModelsTrain | Selection of Differential Distributions with Mixtures of Normals
mixModelsTrain-method | Selection of Differential Distributions with Mixtures of Normals
naiveBayesKernel | Classification Using A Bayes Classifier with Kernel Density Estimates
naiveBayesKernel-method | Classification Using A Bayes Classifier with Kernel Density Estimates
nearestShrunkenCentroidPredictInterface | Interface for 'pamr.predict' Function from 'pamr' CRAN Package
nearestShrunkenCentroidPredictInterface-method | Interface for 'pamr.predict' Function from 'pamr' CRAN Package
nearestShrunkenCentroidSelectionInterface | Interface for 'pamr.listgenes' Function from 'pamr' CRAN Package
nearestShrunkenCentroidSelectionInterface-method | Interface for 'pamr.listgenes' Function from 'pamr' CRAN Package
nearestShrunkenCentroidTrainInterface | Interface for 'pamr.train' Function from 'pamr' CRAN Package
nearestShrunkenCentroidTrainInterface-method | Interface for 'pamr.train' Function from 'pamr' CRAN Package
pamrtrained | Trained pamr Object
pamrtrained-class | Trained pamr Object
performance | Container for Storing Classification Results
performance-method | Container for Storing Classification Results
plotFeatureClasses | Plot Density and Scatterplot for Genes By Class
plotFeatureClasses-method | Plot Density and Scatterplot for Genes By Class
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
rankPlot | Plot Pair-wise Overlap of Ranked Features
rankPlot-method | Plot Pair-wise Overlap of Ranked Features
ResubstituteParams | Parameters for Resubstitution Error Calculation
ResubstituteParams-class | Parameters for Resubstitution Error Calculation
ResubstituteParams-method | Parameters for Resubstitution Error Calculation
runTest | Perform a Single Classification
runTest-method | Perform a Single Classification
runTests | Reproducibly Do Resampling or Leave Out and Cross Validation
runTests-method | Reproducibly Do Resampling or Leave Out and Cross Validation
SelectionParams | Parameters for Feature Selection
SelectionParams-class | Parameters for Feature Selection
SelectionParams-method | Parameters for Feature Selection
selectionPlot | Plot Pair-wise Overlap of Selected Features
selectionPlot-method | Plot Pair-wise Overlap of Selected Features
show-method | Container for Storing Classification Results
subtractFromLocation | Subtract All Feature Measurements from Location
subtractFromLocation-method | Subtract All Feature Measurements from Location
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