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

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Documentation for package ‘MLInterfaces’ version 1.50.0

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

-- A --

acc Assessing classifier performance
acc-method Assessing classifier performance
adaI revised MLearn interface for machine learning

-- B --

baggingI revised MLearn interface for machine learning
balKfold.xvspec generate a partition function for cross-validation, where the partitions are approximately balanced with respect to the distribution of a response variable
BgbmI revised MLearn interface for machine learning
blackboostI revised MLearn interface for machine learning

-- C --

classifierOutput-class Class "classifierOutput"
classifOutput MLInterfaces infrastructure
clusteringOutput-class container for clustering outputs in uniform structure
clustOutput MLInterfaces infrastructure
confuMat Compute the confusion matrix for a classifier.
confuMat-method Compute the confusion matrix for a classifier.
confuMat-methods Compute the confusion matrix for a classifier.
confuTab Compute confusion tables for a confusion matrix.

-- D --

DAB real adaboost (Friedman et al)
daboostCont-class Class "raboostCont" ~~~
dlda revised MLearn interface for machine learning
dlda2 revised MLearn interface for machine learning
dldaI revised MLearn interface for machine learning

-- F --

F1 Assessing classifier performance
F1-method Assessing classifier performance
fn Assessing classifier performance
fn-method Assessing classifier performance
fp Assessing classifier performance
fp-method Assessing classifier performance
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-method Class "classifierOutput"

-- G --

gbm2 revised MLearn interface for machine learning
getConverter container for clustering outputs in uniform structure
getConverter-method container for clustering outputs in uniform structure
getDist container for clustering outputs in uniform structure
getDist-method container for clustering outputs in uniform structure
getGrid MLInterfaces infrastructure
getGrid-method MLInterfaces infrastructure
getVarImp Class "varImpStruct" - collect data on variable importance from various machine learning methods
getVarImp-method Class "varImpStruct" - collect data on variable importance from various machine learning methods
glmI.logistic revised MLearn interface for machine learning
groupIndex MLInterfaces infrastructure

-- H --

hclustI revised MLearn interface for machine learning
hclustWidget shiny-oriented GUI for cluster or classifier exploration

-- K --

kmeansI revised MLearn interface for machine learning
knn.cv2 revised MLearn interface for machine learning
knn.cvI revised MLearn interface for machine learning
knn2 revised MLearn interface for machine learning
knnI revised MLearn interface for machine learning
ksvm2 revised MLearn interface for machine learning
ksvmI revised MLearn interface for machine learning

-- L --

ldaI revised MLearn interface for machine learning
ldaI.predParms revised MLearn interface for machine learning
learnerIn3D Class '"projectedLearner"'
learnerIn3D-method Class '"projectedLearner"'
learnerSchema-class Class "learnerSchema" - convey information on a machine learning function to the MLearn wrapper
lvq revised MLearn interface for machine learning
lvqI revised MLearn interface for machine learning

-- M --

macroF1 Assessing classifier performance
macroF1-method Assessing classifier performance
macroF1-methods Assessing classifier performance
makeLearnerSchema revised MLearn interface for machine learning
membMat MLInterfaces infrastructure
mkfmla real adaboost (Friedman et al)
MLearn revised MLearn interface for machine learning
MLearn-method revised MLearn interface for machine learning
mlearnWidget shiny-oriented GUI for cluster or classifier exploration
MLearn_new revised MLearn interface for machine learning
MLLabel MLInterfaces infrastructure
MLOutput MLInterfaces infrastructure
MLScore MLInterfaces infrastructure

-- N --

naiveBayesI revised MLearn interface for machine learning
nnetI revised MLearn interface for machine learning
nonstandardLearnerSchema-class Class "learnerSchema" - convey information on a machine learning function to the MLearn wrapper

-- P --

pamI revised MLearn interface for machine learning
planarPlot Methods for Function planarPlot in Package 'MLInterfaces'
planarPlot-method Methods for Function planarPlot in Package 'MLInterfaces'
planarPlot-methods Methods for Function planarPlot in Package 'MLInterfaces'
plot Class "varImpStruct" - collect data on variable importance from various machine learning methods
plot-method container for clustering outputs in uniform structure
plot-method Class '"projectedLearner"'
plot-method Class "varImpStruct" - collect data on variable importance from various machine learning methods
plotOne Class '"projectedLearner"'
plotOne-method Class '"projectedLearner"'
plotXvalRDA revised MLearn interface for machine learning
plsda2 revised MLearn interface for machine learning
plsdaI revised MLearn interface for machine learning
plspinHcube shiny app for interactive 3D visualization of mlbench hypercube
precision Assessing classifier performance
precision-method Assessing classifier performance
precision-methods Assessing classifier performance
Predict real adaboost (Friedman et al)
Predict-method real adaboost (Friedman et al)
predict.classifierOutput Predict method for 'classifierOutput' objects
predictions Class "classifierOutput"
predictions-method Class "classifierOutput"
predScore Class "classifierOutput"
predScore-method Class "classifierOutput"
predScores Class "classifierOutput"
predScores-method Class "classifierOutput"
probArray MLInterfaces infrastructure
probMat MLInterfaces infrastructure
projectedLearner-class Class '"projectedLearner"'
projectLearnerToGrid create learned tesselation of feature space after PC transformation

-- Q --

qdaI revised MLearn interface for machine learning
qualScore MLInterfaces infrastructure

-- 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" ~~~
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
recall Assessing classifier performance
recall-method Assessing classifier performance
recall-methods Assessing classifier performance
report Class "varImpStruct" - collect data on variable importance from various machine learning methods
report-method Class "varImpStruct" - collect data on variable importance from various machine learning methods
RObject Class "classifierOutput"
RObject-method Class "classifierOutput"
RObject-method container for clustering outputs in uniform structure
rpartI revised MLearn interface for machine learning

-- S --

sensitivity Assessing classifier performance
sensitivity-method Assessing classifier performance
sensitivity-methods Assessing classifier performance
show-method Class "classifierOutput"
show-method container for clustering outputs in uniform structure
show-method Class "learnerSchema" - convey information on a machine learning function to the MLearn wrapper
show-method Class '"projectedLearner"'
show-method Class "raboostCont" ~~~
show-method Class "varImpStruct" - collect data on variable importance from various machine learning methods
silhouetteVec MLInterfaces infrastructure
sldaI revised MLearn interface for machine learning
SOMBout MLInterfaces infrastructure
somout MLInterfaces infrastructure
specificity Assessing classifier performance
specificity-method Assessing classifier performance
standardMLIConverter revised MLearn interface for machine learning
svm2 revised MLearn interface for machine learning
svmI revised MLearn interface for machine learning

-- T --

testPredictions Class "classifierOutput"
testPredictions-method Class "classifierOutput"
testScores Class "classifierOutput"
testScores-method Class "classifierOutput"
tn Assessing classifier performance
tn-method Assessing classifier performance
tonp real adaboost (Friedman et al)
tp Assessing classifier performance
tp-method Assessing classifier performance
trainInd Class "classifierOutput"
trainInd-method Class "classifierOutput"
trainPredictions Class "classifierOutput"
trainPredictions-method Class "classifierOutput"
trainScores Class "classifierOutput"
trainScores-method Class "classifierOutput"

-- V --

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

-- X --

xvalLoop Cross-validation in clustered computing environments
xvalSpec container for information specifying a cross-validated machine learning exercise
xvalSpec-class container for information specifying a cross-validated machine learning exercise