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

Documentation for package ‘ClassifyR’ version 2.13.14

Help Pages

-- A --

actualClasses	Container for Storing Classification Results
actualClasses-method	Container for Storing Classification Results

-- B --

bartlettSelection	Selection of Differential Variability with Bartlett Statistic
bartlettSelection-method	Selection of Differential Variability with Bartlett Statistic

-- 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
characterOrDataFrame	Union of a Character and a DataFrame
characterOrDataFrame-class	Union of a Character and a DataFrame
classes	Asthma RNA Abundance and Patient Classes
classifyInterface	An Interface for PoiClaClu Package's Classify Function
classifyInterface-method	An 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

-- D --

differentMeansSelection	Selection of Differentially Abundant Features
differentMeansSelection-method	Selection of Differentially Abundant Features
distribution	Get Frequencies of Feature Selection and Sample Errors
distribution-method	Get Frequencies of Feature Selection and Sample Errors
dlda	Trained dlda Object
dlda-class	Trained dlda Object
DLDApredictInterface	An Interface for sparsediscrim Package's dlda Function
DLDApredictInterface-method	An Interface for sparsediscrim Package's dlda Function
DLDAtrainInterface	An Interface for sparsediscrim Package's dlda Function
DLDAtrainInterface-method	An Interface for sparsediscrim Package's dlda Function
DMDselection	Selection of Differential Distributions with Differences in Means or Medians and a Deviation Measure
DMDselection-method	Selection of Differential Distributions with Differences in Means or Medians and a Deviation Measure

-- E --

EasyHardClassifier	Container for a Pair of Trained Classifiers
easyHardClassifier	Two-stage Classification Using Easy-to-collect Data Set and Hard-to-collect data set.
EasyHardClassifier-class	Container for a Pair of Trained Classifiers
EasyHardClassifier-method	Container for a Pair of Trained Classifiers
easyHardClassifierPredict	Two-stage Classification Using Easy-to-collect Data Set and Hard-to-collect data set.
easyHardClassifierPredict-method	Two-stage Classification Using Easy-to-collect Data Set and Hard-to-collect data set.
easyHardClassifierTrain	Two-stage Classification Using Easy-to-collect Data Set and Hard-to-collect data set.
easyHardClassifierTrain-method	Two-stage Classification Using Easy-to-collect Data Set and Hard-to-collect data set.
easyHardFeatures	Extract Chosen Features from an EasyHardClassifier Object
easyHardFeatures-method	Extract Chosen Features from an EasyHardClassifier Object
edgeRselection	Feature Selection Based on Differential Expression for Count Data
edgeRselection-method	Feature Selection Based on Differential Expression for Count Data
edgesToHubNetworks	Convert a Two-column Matrix or Data Frame into a Hub Node List
elasticNetFeatures	Extract Vectors of Ranked and Selected Features From an Elastic Net GLM Object
elasticNetFeatures-method	Extract Vectors of Ranked and Selected Features From an Elastic Net GLM Object
elasticNetGLMinterface	An Interface for glmnet Package's glmnet Function
elasticNetGLMpredictInterface	An Interface for glmnet Package's glmnet Function
elasticNetGLMpredictInterface-method	An Interface for glmnet Package's glmnet Function
elasticNetGLMtrainInterface	An Interface for glmnet Package's glmnet Function
elasticNetGLMtrainInterface-method	An Interface for glmnet Package's glmnet Function

-- F --

featureNames	Container for Storing Classification Results
featureNames-method	Container for Storing Classification Results
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
FeatureSetCollectionOrNULL	Union of a FeatureSetCollection and NULL
FeatureSetCollectionOrNULL-class	Union of a FeatureSetCollection and NULL
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.
fisherDiscriminant	Classification Using Fisher's LDA
fisherDiscriminant-method	Classification Using Fisher's LDA
forestFeatures	Extract Vectors of Ranked and Selected Features From a Random Forest Object
forestFeatures-method	Extract Vectors of Ranked and Selected Features From a Random Forest Object
functionOrList	Union of Functions and List of Functions
functionOrList-class	Union of Functions and List of Functions
functionOrNULL	Union of A Function and NULL
functionOrNULL-class	Union of A Function and NULL

-- G --

getLocationsAndScales	Calculate Location and Scale
getLocationsAndScales-method	Calculate Location and Scale

-- I --

integerOrNumeric	Union of a Integer and a Numeric
integerOrNumeric-class	Union of a Integer and a Numeric
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

-- K --

kNNinterface	An Interface for class Package's knn Function
kNNinterface-method	An Interface for class Package's knn Function
KolmogorovSmirnovSelection	Selection of Differential Distributions with Kolmogorov-Smirnov Distance
KolmogorovSmirnovSelection-method	Selection of Differential Distributions with Kolmogorov-Smirnov Distance
kTSPclassifier	Classification Using k Pairs of Features With Relative Differences Between Classes
kTSPclassifier-method	Classification Using k Pairs of Features With Relative Differences Between Classes
KullbackLeiblerSelection	Selection of Differential Distributions with Kullback-Leibler Distance
KullbackLeiblerSelection-method	Selection of Differential Distributions with Kullback-Leibler Distance

-- L --

length-method	Container for Storing A Collection of Sets
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 Abundant Features
limmaSelection-method	Selection of Differentially Abundant Features
listOrCharacterOrNULL	Union of a List and a Character Vector and NULL
listOrCharacterOrNULL-class	Union of a List and a Character Vector and NULL
listOrNULL	Union of a List and NULL
listOrNULL-class	Union of a List and NULL

-- M --

measurements	Asthma RNA Abundance and Patient Classes
mixmodels	Classification based on Differential Distribution utilising Mixtures of Normals
MixModelsListsSet	Container for a List of Lists Containing Mixture Models
MixModelsListsSet-class	Container for a List of Lists Containing Mixture Models
MixModelsListsSet-method	Container for a List of Lists Containing Mixture Models
mixModelsPredict	Classification based on Differential Distribution utilising Mixtures of Normals
mixModelsPredict-method	Classification based on Differential Distribution utilising Mixtures of Normals
mixModelsTrain	Classification based on Differential Distribution utilising Mixtures of Normals
mixModelsTrain-method	Classification based on Differential Distribution utilising Mixtures of Normals
models	Container for Storing Classification Results
models-method	Container for Storing Classification Results
multnet	Trained multnet Object
multnet-class	Trained multnet Object

-- N --

naiveBayesKernel	Classification Using A Bayes Classifier with Kernel Density Estimates
naiveBayesKernel-method	Classification Using A Bayes Classifier with Kernel Density Estimates
networkCorrelationsSelection	Selection of Differentially Correlated Hub Sub-networks
networkCorrelationsSelection-method	Selection of Differentially Correlated Hub Sub-networks
NSCpredictInterface	Interface for 'pamr.predict' Function from 'pamr' CRAN Package
NSCpredictInterface-method	Interface for 'pamr.predict' Function from 'pamr' CRAN Package
NSCselectionInterface	Interface for 'pamr.listgenes' Function from 'pamr' CRAN Package
NSCselectionInterface-method	Interface for 'pamr.listgenes' Function from 'pamr' CRAN Package
NSCtrainInterface	Interface for 'pamr.train' Function from 'pamr' CRAN Package
NSCtrainInterface-method	Interface for 'pamr.train' Function from 'pamr' CRAN Package

-- P --

pairsDifferencesSelection	Selection of Pairs of Features that are Different Between Classes
pairsDifferencesSelection-method	Selection of Pairs of Features that are Different Between Classes
pamrtrained	Trained pamr Object
pamrtrained-class	Trained pamr Object
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
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
previousSelection	Automated Selection of Previously Selected Features
previousSelection-method	Automated Selection of Previously Selected Features
previousTrained	Automated Usage of Previously Created Classifiers
previousTrained-method	Automated Usage of Previously Created Classifiers

-- R --

randomForest	Trained randomForest Object
randomForest-class	Trained randomForest Object
randomForestInterface	An Interface for randomForest Package's randomForest Function
randomForestPredictInterface	An Interface for randomForest Package's randomForest Function
randomForestPredictInterface-method	An Interface for randomForest Package's randomForest Function
randomForestTrainInterface	An Interface for randomForest Package's randomForest Function
randomForestTrainInterface-method	An Interface for randomForest Package's randomForest Function
rankingPlot	Plot Pair-wise Overlap of Ranked Features
rankingPlot-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
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
runTestEasyHard	Perform a Single Classification
runTestEasyHard-method	Perform a Single Classification
runTests	Reproducibly Run Various Kinds of Cross-Validation
runTests-method	Reproducibly Run Various Kinds of Cross-Validation
runTestsEasyHard	Reproducibly Run Various Kinds of Cross-Validation
runTestsEasyHard-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 or Selection Size Distribution of Selected Features
selectionPlot-method	Plot Pair-wise Overlap or Selection Size Distribution of Selected Features
SelectParams	Parameters for Feature Selection
SelectParams-class	Parameters for Feature Selection
SelectParams-method	Parameters for Feature Selection
SelectResult	Container for Storing Feature Selection Results
SelectResult-class	Container for Storing Feature Selection Results
SelectResult-method	Container for Storing Feature Selection Results
show-method	Container for Storing Classification Results
show-method	Container for a Pair of Trained Classifiers
show-method	Container for Storing A Collection of Sets
show-method	Container for Storing Feature Selection Results
subtractFromLocation	Subtract Numeric Feature Measurements from a Location
subtractFromLocation-method	Subtract Numeric Feature Measurements from a Location
svm	Trained svm Object
svm-class	Trained svm Object
SVMpredictInterface	An Interface for e1071 Package's Support Vector Machine Classifier.
SVMpredictInterface-method	An Interface for e1071 Package's Support Vector Machine Classifier.
SVMtrainInterface	An Interface for e1071 Package's Support Vector Machine Classifier.
SVMtrainInterface-method	An Interface for e1071 Package's Support Vector Machine Classifier.

-- T --

totalPredictions	Container for Storing Classification Results
totalPredictions-method	Container for Storing Classification Results
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