Package index

All functions

ClassifyResult ClassifyResult-class ClassifyResult,DataFrame,character,characterOrDataFrame-method show,ClassifyResult-method sampleNames sampleNames,ClassifyResult-method predictions predictions,ClassifyResult-method actualOutcome actualOutcome,ClassifyResult-method features features,ClassifyResult-method models models,ClassifyResult-method finalModel finalModel,ClassifyResult-method performance performance,ClassifyResult-method tunedParameters tunedParameters,ClassifyResult-method totalPredictions totalPredictions,ClassifyResult-method ClassifyResult,DataFrame,character-method allFeatureNames allFeatureNames,ClassifyResult-method chosenFeatureNames chosenFeatureNames,ClassifyResult-method

Container for Storing Classification Results

CrossValParams()

Parameters for Cross-validation Specification

FeatureSetCollection-class FeatureSetCollection FeatureSetCollection,list-method length,FeatureSetCollection-method show,FeatureSetCollection-method [,FeatureSetCollection,numeric,missing,ANY-method [[,FeatureSetCollection,ANY,missing-method

Container for Storing A Collection of Sets

HuRI interactors

Human Reference Interactome

METABRICclinical clinical

METABRIC Clinical Data

ModellingParams()

Parameters for Data Modelling Specification

PredictParams PredictParams-class PredictParams,missing-method PredictParams,characterOrFunction-method show,PredictParams-method

Parameters for Classifier Prediction

ROCplot(<ClassifyResult>) ROCplot(<list>)

Plot Receiver Operating Curve Graphs for Classification Results

SelectParams SelectParams-class SelectParams,missing-method SelectParams,characterOrList-method show,SelectParams-method

Parameters for Feature Selection

TrainParams TrainParams-class TrainParams,missing-method TrainParams,characterOrFunction-method show,TrainParams-method

Parameters for Classifier Training

TransformParams TransformParams-class TransformParams,ANY-method TransformParams,character-method show,TransformParams-method

Parameters for Data Transformation

asthma measurements classes

Asthma RNA Abundance and Patient Classes

available()

List Available Feature Selection and Classification Approaches

calcExternalPerformance(<factor>,<factor>) calcExternalPerformance(<Surv>,<numeric>) calcExternalPerformance(<factor>,<tabular>) calcCVperformance(<ClassifyResult>) performanceTable() easyHard(<MultiAssayExperimentOrList>)

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(<DataFrame>) crossValidate(<MultiAssayExperimentOrList>) crossValidate(<data.frame>) crossValidate(<matrix>) train(<matrix>) train(<data.frame>) train(<DataFrame>) train(<list>) train(<MultiAssayExperiment>) predict(<trainedByClassifyR>)

Cross-validation to evaluate classification performance.

distribution distribution,ClassifyResult-method

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(<matrix>) featureSetSummary(<DataFrame>) featureSetSummary(<MultiAssayExperiment>)

Transform a Table of Feature Abundances into a Table of Feature Set Abundances.

interactorDifferences(<matrix>) interactorDifferences(<DataFrame>) interactorDifferences(<MultiAssayExperiment>)

Convert Individual Features into Differences Between Binary Interactors Based on Known Sub-networks

performancePlot(<ClassifyResult>) performancePlot(<list>)

Plot Performance Measures for Various Classifications

plotFeatureClasses(<matrix>) plotFeatureClasses(<DataFrame>) plotFeatureClasses(<MultiAssayExperiment>)

Plot Density, Scatterplot, Parallel Plot or Bar Chart for Features By Class

precisionPathwaysTrain(<MultiAssayExperimentOrList>) precisionPathwaysPredict(<PrecisionPathways>,<MultiAssayExperimentOrList>)

Precision Pathways for Sample Prediction Based on Prediction Confidence.

calcCostsAndPerformance() summary(<PrecisionPathways>) bubblePlot() flowchart() strataPlot()

Various Functions for Evaluating Precision Pathways

prepareData(<matrix>) prepareData(<data.frame>) prepareData(<DataFrame>) prepareData(<MultiAssayExperiment>) prepareData(<list>)

Convert Different Data Classes into DataFrame and Filter Features

rankingPlot(<ClassifyResult>) rankingPlot(<list>)

Plot Pair-wise Overlap of Ranked Features

runTest(<matrix>) runTest(<DataFrame>) runTest(<MultiAssayExperiment>)

Perform a Single Classification

runTests(<matrix>) runTests(<DataFrame>) runTests(<MultiAssayExperiment>)

Reproducibly Run Various Kinds of Cross-Validation

samplesMetricMap(<ClassifyResult>) samplesMetricMap(<list>) samplesMetricMap(<matrix>)

Plot a Grid of Sample-wise Predictive Metrics

samplesSplits() splitsTestInfo()

Split Sample Indexes into Training and Test Partitions for Cross-validation Taking Into Account Classes.

selectionPlot(<ClassifyResult>) selectionPlot(<list>)

Plot Pair-wise Overlap, Variable Importance or Selection Size Distribution of Selected Features