# Uniform interfaces to R machine learning procedures for data in Bioconductor containers

## Documentation for package ‘MLInterfaces’ version 1.14.1

## User Guides and Package Vignettes

Read overview or browse directory.

## Help Pages

A B C D E F G H I K L M N O P Q R S T V W X

## -- A --

adaI | revised MLearn interface for machine learning
agnes-class | Class "classifOutput": container for output of classification procedures in R
agnesB | An interface to various unsupervised machine learning methods for ExpressionSets
agnesB,ExpressionSet,numeric-method | An interface to various unsupervised machine learning methods for ExpressionSets
allClass | An interface to various machine learning methods for ExpressionSets
allClass,classifOutput-method | An interface to various machine learning methods for ExpressionSets

## -- B --

bagging-class | Class "classifOutput": container for output of classification procedures in R
baggingB | An interface to various machine learning methods for ExpressionSets
baggingB,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
baggingI | revised MLearn interface for machine learning
balKfold | support for cross-validatory machine learning with ExpressionSets
balKfold.xvspec | generate a partition function for cross-validation, where the partitions are approximately balanced with respect to the distribution of a response variable
bclust-class | Class "clustOutput" container for cluster analysis results
bclustB | An interface to various unsupervised machine learning methods for ExpressionSets
bclustB,ExpressionSet,numeric-method | An interface to various unsupervised machine learning methods for ExpressionSets

## -- C --

chkMLInterfaceProc | MLInterfaces infrastructure
claraB | An interface to various unsupervised machine learning methods for ExpressionSets
claraB,ExpressionSet,numeric-method | An interface to various unsupervised machine learning methods for ExpressionSets
classbagg-class | Class "classifOutput": container for output of classification procedures in R
classifierOutput-class | Class "classifierOutput"
classifOutput | Class "classifOutput": container for output of classification procedures in R
classifOutput-class | Class "classifOutput": container for output of classification procedures in R
clustOutput-class | Class "clustOutput" container for cluster analysis results
cmeansB | An interface to various unsupervised machine learning methods for ExpressionSets
cmeansB,ExpressionSet,numeric-method | An interface to various unsupervised machine learning methods for ExpressionSets
confuMat | Compute the confusion matrix for a classifier.
confuMat,classifierOutput,character-method | Compute the confusion matrix for a classifier.
confuMat,classifierOutput,missing-method | Compute the confusion matrix for a classifier.
confuMat,classifierOutput-method | Compute the confusion matrix for a classifier.
confuMat,classifOutput,character-method | Compute the confusion matrix for a classifier.
confuMat,classifOutput,missing-method | Compute the confusion matrix for a classifier.
confuMat,classifOutput-method | Compute the confusion matrix for a classifier.
confuMat-methods | Compute the confusion matrix for a classifier.
confuMatTrain | Methods for Function MLearn in Package ‘MLInterfaces’
confuMatTrain,classifOutput-method | Methods for Function MLearn in Package ‘MLInterfaces’
cshell-class | Class "classifOutput": container for output of classification procedures in R
cshellB | An interface to various unsupervised machine learning methods for ExpressionSets
cshellB,ExpressionSet,numeric-method | An interface to various unsupervised machine learning methods for ExpressionSets
cvB | An interface to various machine learning methods for ExpressionSets
cvB,ExpressionSet,character-method | An interface to various machine learning methods for ExpressionSets

## -- D --

DAB | real adaboost (Friedman et al)
daboostCont-class | Class "raboostCont" ~~~
diana-class | Class "classifOutput": container for output of classification procedures in R
dianaB | An interface to various unsupervised machine learning methods for ExpressionSets
dianaB,ExpressionSet,numeric-method | An interface to various unsupervised machine learning methods for ExpressionSets
dist-class | Class "classifOutput": container for output of classification procedures in R
distMat | An interface to various unsupervised machine learning methods for ExpressionSets
distMat,MLOutput-method | An interface to various machine learning methods for ExpressionSets
dlda | revised MLearn interface for machine learning
dlda2 | revised MLearn interface for machine learning
dldaI | revised MLearn interface for machine learning

## -- E --

es2df | Methods for Function MLearn in Package ‘MLInterfaces’

## -- F --

fannyB | An interface to various unsupervised machine learning methods for ExpressionSets
fannyB,ExpressionSet,numeric-method | An interface to various unsupervised machine learning methods for ExpressionSets
fclust-class | Class "clustOutput" container for cluster analysis results
fs.absT | support for feature selection in cross-validation
fs.probT | support for feature selection in cross-validation
fs.topVariance | support for feature selection in cross-validation
fsHistory | extract history of feature selection for a cross-validated machine learner
fsHistory,classifierOutput-method | Class "classifierOutput"

## -- G --

gbm-class | Class "classifOutput": container for output of classification procedures in R
gbmB | An interface to various machine learning methods for ExpressionSets
gbmB,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
getGrid | MLInterfaces infrastructure
getGrid,data.frame-method | MLInterfaces infrastructure
getGrid,ExpressionSet-method | MLInterfaces infrastructure
getVarImp | Class "varImpStruct" - collect data on variable importance from various machine learning methods
getVarImp,classifierOutput,logical-method | Class "varImpStruct" - collect data on variable importance from various machine learning methods
getVarImp,classifierOutput,missing-method | Class "varImpStruct" - collect data on variable importance from various machine learning methods
getVarImp,classifOutput,logical-method | Class "varImpStruct" - collect data on variable importance from various machine learning methods
glmI.logistic | revised MLearn interface for machine learning
groupIndex-class | Class "classifOutput": container for output of classification procedures in R

## -- H --

hclust-class | Class "clustOutput" container for cluster analysis results
hclustB | An interface to various unsupervised machine learning methods for ExpressionSets
hclustB,ExpressionSet,missing,numeric-method | An interface to various unsupervised machine learning methods for ExpressionSets
hclustB,ExpressionSet,numeric,ANY-method | An interface to various unsupervised machine learning methods for ExpressionSets
hclustB,ExpressionSet,numeric,missing-method | An interface to various unsupervised machine learning methods for ExpressionSets

## -- I --

ica-class | Class "classifOutput": container for output of classification procedures in R
ipredknn-class | Class "classifOutput": container for output of classification procedures in R
ipredknnB | An interface to various machine learning methods for ExpressionSets
ipredknnB,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
isoMDSB | An interface to various unsupervised machine learning methods for ExpressionSets

## -- K --

Kfold | for given n, generate a K-fold partition of 1:n
kmeans-class | Class "classifOutput": container for output of classification procedures in R
kmeansB | An interface to various unsupervised machine learning methods for ExpressionSets
kmeansB,ExpressionSet,numeric-method | An interface to various unsupervised machine learning methods for ExpressionSets
knn.cv2 | revised MLearn interface for machine learning
knn.cvI | revised MLearn interface for machine learning
knn1B | An interface to various machine learning methods for ExpressionSets
knn1B,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
knn2 | revised MLearn interface for machine learning
knnB | An interface to various machine learning methods for ExpressionSets
knnB,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
knnI | revised MLearn interface for machine learning
knnP | An interface to various machine learning methods for ExpressionSets
knnP-class | Class "classifOutput": container for output of classification procedures in R
ksvmI | revised MLearn interface for machine learning

## -- L --

last.warning | An interface to various machine learning methods for ExpressionSets
lca-class | Class "classifOutput": container for output of classification procedures in R
lcaB | An interface to various machine learning methods for ExpressionSets
lcaB,ExpressionSet,numeric-method | An interface to various machine learning methods for ExpressionSets
lda-class | Class "classifOutput": container for output of classification procedures in R
ldaB | An interface to various machine learning methods for ExpressionSets
ldaB,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
ldaI | revised MLearn interface for machine learning
learnerSchema-class | Class "learnerSchema" - convey information on a machine learning function to the MLearn wrapper
logitboost-class | Class "classifOutput": container for output of classification procedures in R
logitboostB | An interface to various machine learning methods for ExpressionSets
logitboostB,ExpressionSet,character,integer,numeric-method | An interface to various machine learning methods for ExpressionSets
lvq | revised MLearn interface for machine learning
lvq1B | An interface to various machine learning methods for ExpressionSets
lvq1B,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
lvq2B | An interface to various machine learning methods for ExpressionSets
lvq2B,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
lvq3B | An interface to various machine learning methods for ExpressionSets
lvq3B,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
lvqI | revised MLearn interface for machine learning

## -- M --

makeLearnerSchema | revised MLearn interface for machine learning
membMat-class | Class "classifOutput": container for output of classification procedures in R
mkfmla | real adaboost (Friedman et al)
MLearn | revised MLearn interface for machine learning
MLearn,formula,data.frame,character,numeric,ANY-method | Methods for Function MLearn in Package ‘MLInterfaces’
MLearn,formula,data.frame,character,numeric-method | Methods for Function MLearn in Package ‘MLInterfaces’
MLearn,formula,data.frame,learnerSchema,numeric,missing-method | revised MLearn interface for machine learning
MLearn,formula,data.frame,learnerSchema,xvalSpec,missing-method | revised MLearn interface for machine learning
MLearn,formula,ExpressionSet,character,numeric,ANY-method | Methods for Function MLearn in Package ‘MLInterfaces’
MLearn,formula,ExpressionSet,character,numeric,missing-method | revised MLearn interface for machine learning
MLearn,formula,ExpressionSet,character,numeric-method | Methods for Function MLearn in Package ‘MLInterfaces’
MLearn,formula,ExpressionSet,learnerSchema,numeric,missing-method | revised MLearn interface for machine learning
MLearn,formula,ExpressionSet,learnerSchema,xvalSpec,missing-method | revised MLearn interface for machine learning
MLearn-methods | Methods for Function MLearn in Package ‘MLInterfaces’
MLearn-OLD | Methods for Function MLearn in Package ‘MLInterfaces’
MLearn_new | revised MLearn interface for machine learning
MLLabel | Class "classifOutput": container for output of classification procedures in R
MLLabel-class | Class "classifOutput": container for output of classification procedures in R
MLOutput | Class "classifOutput": container for output of classification procedures in R
MLOutput-class | Class "classifOutput": container for output of classification procedures in R
MLScore | Class "classifOutput": container for output of classification procedures in R
MLScore-class | Class "classifOutput": container for output of classification procedures in R

## -- N --

naiveBayes-class | Class "classifOutput": container for output of classification procedures in R
naiveBayesB | An interface to various machine learning methods for ExpressionSets
naiveBayesB,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
naiveBayesI | revised MLearn interface for machine learning
newGroupIndex | MLInterfaces infrastructure
newMembMat | MLInterfaces infrastructure
newPredClass | MLInterfaces infrastructure
newProbArray | MLInterfaces infrastructure
newProbMat | MLInterfaces infrastructure
newQualScore | MLInterfaces infrastructure
newSilhouetteVec | MLInterfaces infrastructure
nnet.formula-class | Class "classifOutput": container for output of classification procedures in R
nnetB | An interface to various machine learning methods for ExpressionSets
nnetB,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
nnetI | revised MLearn interface for machine learning
nonstandardLearnerSchema-class | Class "learnerSchema" - convey information on a machine learning function to the MLearn wrapper
nsc-class | Class "classifOutput": container for output of classification procedures in R

## -- O --

olvq1B | An interface to various machine learning methods for ExpressionSets
olvq1B,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets

## -- P --

pam-class | Class "classifOutput": container for output of classification procedures in R
pamB | An interface to various unsupervised machine learning methods for ExpressionSets
pamB,ExpressionSet,numeric-method | An interface to various unsupervised machine learning methods for ExpressionSets
pamr-class | Class "classifOutput": container for output of classification procedures in R
pamrB | An interface to various machine learning methods for ExpressionSets
pamrB,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
planarPlot | Methods for Function planarPlot in Package ‘MLInterfaces’
planarPlot,classifOutput,data.frame,character-method | Methods for Function planarPlot in Package ‘MLInterfaces’
planarPlot,classifOutput,ExpressionSet,character-method | Methods for Function planarPlot in Package ‘MLInterfaces’
planarPlot-methods | Methods for Function planarPlot in Package ‘MLInterfaces’
plot,varImpStruct,ANY-method | Class "varImpStruct" - collect data on variable importance from various machine learning methods
plot,varImpStruct-method | Class "varImpStruct" - collect data on variable importance from various machine learning methods
plotXvalRDA | revised MLearn interface for machine learning
prcomp-class | Class "classifOutput": container for output of classification procedures in R
predClass-class | Class "classifOutput": container for output of classification procedures in R
Predict | real adaboost (Friedman et al)
Predict,daboostCont-method | real adaboost (Friedman et al)
Predict,raboostCont-method | real adaboost (Friedman et al)
predict.knnP | MLInterfaces infrastructure
predLabels | An interface to various machine learning methods for ExpressionSets
predLabels,classifOutput-method | An interface to various machine learning methods for ExpressionSets
predLabels,MLOutput-method | An interface to various machine learning methods for ExpressionSets
predLabelsTr | Methods for Function MLearn in Package ‘MLInterfaces’
predLabelsTr,classifOutput-method | Methods for Function MLearn in Package ‘MLInterfaces’
print.knnP | MLInterfaces infrastructure
probArray-class | Class "classifOutput": container for output of classification procedures in R
probMat-class | Class "classifOutput": container for output of classification procedures in R

## -- Q --

qda-class | Class "classifOutput": container for output of classification procedures in R
qdaB | An interface to various machine learning methods for ExpressionSets
qdaB,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
qdaI | revised MLearn interface for machine learning
qualScore-class | Class "classifOutput": container for output of classification procedures in R

## -- R --

RAB | real adaboost (Friedman et al)
rab | revised MLearn interface for machine learning
RAB4es | real adaboost (Friedman et al)
RABI | revised MLearn interface for machine learning
raboostCont-class | Class "raboostCont" ~~~
randomForest-class | Class "classifOutput": container for output of classification procedures in R
randomForestB | An interface to various machine learning methods for ExpressionSets
randomForestB,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
randomForestI | revised MLearn interface for machine learning
rdacvI | revised MLearn interface for machine learning
rdacvML | revised MLearn interface for machine learning
rdaI | revised MLearn interface for machine learning
rdaML | revised MLearn interface for machine learning
report | Class "varImpStruct" - collect data on variable importance from various machine learning methods
report,varImpStruct-method | Class "varImpStruct" - collect data on variable importance from various machine learning methods
RObject | An interface to various machine learning methods for ExpressionSets
RObject,classifierOutput-method | Class "classifierOutput"
RObject,MLOutput-method | An interface to various machine learning methods for ExpressionSets
rpart-class | Class "classifOutput": container for output of classification procedures in R
rpartB | An interface to various machine learning methods for ExpressionSets
rpartB,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
rpartI | revised MLearn interface for machine learning

## -- S --

show,classifierOutput-method | Class "classifierOutput"
show,clustOutput-method | Class "clustOutput" container for cluster analysis results
show,learnerSchema-method | Class "learnerSchema" - convey information on a machine learning function to the MLearn wrapper
show,membMat-method | An interface to various machine learning methods for ExpressionSets
show,MLOutput-method | An interface to various machine learning methods for ExpressionSets
show,probArray-method | An interface to various machine learning methods for ExpressionSets
show,probMat-method | An interface to various machine learning methods for ExpressionSets
show,qualScore-method | An interface to various machine learning methods for ExpressionSets
show,raboostCont-method | Class "raboostCont" ~~~
show,silhouetteVec-method | An interface to various machine learning methods for ExpressionSets
show,SOMBout-method | An interface to self-organizing map methods for ExpressionSets
show,somout-method | An interface to self-organizing map methods for ExpressionSets
show,varImpStruct-method | Class "varImpStruct" - collect data on variable importance from various machine learning methods
silhouetteB | An interface to various unsupervised machine learning methods for ExpressionSets
silhouetteB,classifOutput-method | Class "classifOutput": container for output of classification procedures in R
silhouetteB,clustOutput-method | Class "clustOutput" container for cluster analysis results
silhouetteVec-class | Class "classifOutput": container for output of classification procedures in R
slda-class | Class "classifOutput": container for output of classification procedures in R
sldaB | An interface to various machine learning methods for ExpressionSets
sldaB,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
sldaI | revised MLearn interface for machine learning
SOMB | An interface to self-organizing map methods for ExpressionSets
somB | An interface to self-organizing map methods for ExpressionSets
SOMB,ExpressionSet,character-method | An interface to self-organizing map methods for ExpressionSets
somB,ExpressionSet,character-method | An interface to self-organizing map methods for ExpressionSets
SOMBout-class | Class "classifOutput": container for output of classification procedures in R
somout-class | An interface to self-organizing map methods for ExpressionSets
standardMLIConverter | revised MLearn interface for machine learning
stat.diag.daB | An interface to various machine learning methods for ExpressionSets
stat.diag.daB,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
svm-class | Class "classifOutput": container for output of classification procedures in R
svmB | An interface to various machine learning methods for ExpressionSets
svmB,ExpressionSet,character,integer-method | An interface to various machine learning methods for ExpressionSets
svmI | revised MLearn interface for machine learning

## -- T --

tellMLearnMethods | Methods for Function MLearn in Package ‘MLInterfaces’
testPredictions | Class "classifierOutput"
testPredictions,classifierOutput-method | Class "classifierOutput"
testScores | Class "classifierOutput"
testScores,classifierOutput-method | Class "classifierOutput"
tonp | real adaboost (Friedman et al)
trainInds | An interface to various unsupervised machine learning methods for ExpressionSets
trainInds,classifOutput-method | An interface to various machine learning methods for ExpressionSets
trainPredictions | Class "classifierOutput"
trainPredictions,classifierOutput-method | Class "classifierOutput"

## -- V --

varImpStruct-class | Class "varImpStruct" - collect data on variable importance from various machine learning methods

## -- W --

wrapClust | MLInterfaces infrastructure

## -- X --

xval | support for cross-validatory machine learning with ExpressionSets
xval,ExpressionSet,character,genericFunction,character,integer-method | support for cross-validatory machine learning with ExpressionSets
xval,ExpressionSet,character,genericFunction,character,missing-method | support for cross-validatory machine learning with ExpressionSets
xval,ExpressionSet,character,nonstandardGeneric,character,integer-method | support for cross-validatory machine learning with ExpressionSets
xval,ExpressionSet,character,nonstandardGeneric,character,missing-method | support for cross-validatory machine learning with ExpressionSets
xval-methods | support for cross-validatory machine learning with ExpressionSets
xvalLoop | Cross-validation in clustered computing environments
xvalLoop,ANY-method | Cross-validation in clustered computing environments
xvalLoop-methods | Cross-validation in clustered computing environments
xvalML | support for cross-validatory machine learning with ExpressionSets
xvalML,formula,ExpressionSet,character,character,missing,missing,missing,function,missing,missing,missing-method | support for cross-validatory machine learning with ExpressionSets
xvalML,formula,ExpressionSet,character,character,missing,missing,missing,function,numeric,missing,missing-method | support for cross-validatory machine learning with ExpressionSets
xvalML,formula,ExpressionSet,character,character,missing,missing,missing,missing,missing,missing,missing-method | support for cross-validatory machine learning with ExpressionSets
xvalML,formula,ExpressionSet,character,character,missing,missing,missing,missing,missing,missing-method | support for cross-validatory machine learning with ExpressionSets
xvalML,formula,ExpressionSet,character,character,missing-method | support for cross-validatory machine learning with ExpressionSets
xvalML,formula,ExpressionSet,character,character,numeric,ANY,ANY,ANY,ANY,ANY,ANY-method | support for cross-validatory machine learning with ExpressionSets
xvalML,formula,ExpressionSet,character,character,numeric,ANY,ANY,ANY,ANY,ANY-method | support for cross-validatory machine learning with ExpressionSets
xvalML,formula,ExpressionSet,character,character,numeric-method | support for cross-validatory machine learning with ExpressionSets
xvalSpec | container for information specifying a cross-validated machine learning exercise
xvalSpec-class | container for information specifying a cross-validated machine learning exercise