Rapid Implementation of Machine Learning Algorithms for Genomic Data

[Up] [Top]

Documentation for package ‘exprso’ version 0.1.8

Help Pages

A B C D E F G M P R S T V misc

-- A --

array Sample ExprsBinary Data
arrayExprs Import Data as ExprsArray
arrayMulti Sample ExprsMulti Data

-- B --

build Build Classifiers
build. Workhorse for build Methods
buildANN Build Classifiers
buildANN-method Build Classifiers
buildDNN Build Classifiers
buildDNN-method Build Classifiers
buildEnsemble Build Ensemble
buildEnsemble-method Build Ensemble
buildLDA Build Classifiers
buildLDA-method Build Classifiers
buildNB Build Classifiers
buildNB-method Build Classifiers
buildRF Build Classifiers
buildRF-method Build Classifiers
buildSVM Build Classifiers
buildSVM-method Build Classifiers

-- C --

calcMonteCarlo Calculate 'plMonteCarlo' Performance
calcNested Calculate 'plNested' Performance
calcStats Calculate Classifier Performance
calcStats-method Calculate Classifier Performance
check.ctrlGS Check 'ctrlGS' Arguments
compare Compare 'ExprsArray' Objects
compare-method Compare 'ExprsArray' Objects
conjoin Combine 'exprso' Objects
conjoin-method Combine 'exprso' Objects
ctrlFeatureSelect Manage 'fs' Arguments
ctrlGridSearch Manage 'plGrid' Arguments
ctrlSplitSet Manage 'split' Arguments

-- D --

defaultArg Set an args List Element to Default Value
doMulti Perform "1 vs. all" Task
doMulti-method Perform "1 vs. all" Task

-- E --

ExprsArray-class An S4 class to store feature and annotation data
ExprsBinary-class An S4 class to store feature and annotation data
ExprsEnsemble-class An S4 class to store multiple classification models
ExprsMachine-class An S4 class to store the classification model
ExprsModel-class An S4 class to store the classification model
ExprsModule-class An S4 class to store the classification model
ExprsMulti-class An S4 class to store feature and annotation data
exprso-predict Predict Class Labels
ExprsPipeline-class An S4 class to store models built during high-throughput learning
ExprsPredict-class An S4 class to store class predictions

-- F --

forceArg Force an args List Element to Value
fs Perform Feature Selection
fs. Workhorse for fs Methods
fsANOVA Perform Feature Selection
fsANOVA-method Perform Feature Selection
fsEbayes Perform Feature Selection
fsEbayes-method Perform Feature Selection
fsInclude Perform Feature Selection
fsInclude-method Perform Feature Selection
fsMrmre Perform Feature Selection
fsMrmre-method Perform Feature Selection
fsNULL Perform Feature Selection
fsNULL-method Perform Feature Selection
fsPathClassRFE Perform Feature Selection
fsPathClassRFE-method Perform Feature Selection
fsPrcomp Perform Feature Selection
fsPrcomp-method Perform Feature Selection
fsSample Perform Feature Selection
fsSample-method Perform Feature Selection
fsStats Perform Feature Selection
fsStats-method Perform Feature Selection

-- G --

getArgs Build an args List
getFeatures Retrieve Feature Set
getFeatures-method An S4 class to store feature and annotation data
getFeatures-method An S4 class to store multiple classification models
getFeatures-method An S4 class to store the classification model
getFeatures-method An S4 class to store models built during high-throughput learning
GSE2eSet Convert GSE to eSet

-- M --

makeGridFromArgs Build Argument Grid
modCluster Cluster Subjects
modCluster-method Cluster Subjects
modFilter Hard Filter Data
modFilter-method Hard Filter Data
modHistory Duplicate Feature Selection History
modHistory-method Duplicate Feature Selection History
modNormalize Normalize Data
modNormalize-method Normalize Data
modSubset Tidy Subset Wrapper
modSwap Swap Case Subjects
modSwap-method Swap Case Subjects
modTransform Log Transform Data
modTransform-method Log Transform Data

-- P --

pipeFilter Filter 'ExprsPipeline' Object
pipeFilter-method Filter 'ExprsPipeline' Object
pipeSubset Tidy Subset Wrapper
pipeUnboot Rename "boot" Column
pipeUnboot-method Rename "boot" Column
plCV Perform Simple Cross-Validation
plGrid Perform High-Throughput Classification
plGridMulti Perform High-Throughput Classification
plMonteCarlo Monte Carlo Cross-Validation
plNested Nested Cross-Validation
plot-method An S4 class to store feature and annotation data
predict-method Predict Class Labels

-- R --

reRank Serialize "1 vs. all" Feature Selection

-- S --

show-method An S4 class to store feature and annotation data
show-method An S4 class to store multiple classification models
show-method An S4 class to store the classification model
show-method An S4 class to store models built during high-throughput learning
show-method An S4 class to store class predictions
split split 'ExprsArray' objects
splitSample split 'ExprsArray' objects
splitSample-method split 'ExprsArray' objects
splitStratify split 'ExprsArray' objects
splitStratify-method split 'ExprsArray' objects
subset-method An S4 class to store feature and annotation data
subset-method An S4 class to store models built during high-throughput learning
summary-method An S4 class to store feature and annotation data
summary-method An S4 class to store models built during high-throughput learning

-- T --

testSet Extract Validation Set
trainingSet Extract Training Set

-- V --

validationSet Extract Validation Set

-- misc --

$-method An S4 class to store feature and annotation data
$-method An S4 class to store models built during high-throughput learning
[-method An S4 class to store feature and annotation data
[-method An S4 class to store models built during high-throughput learning