MLInterfaces v1.46.0

by Vince Carey

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

Uniform interfaces to machine learning code for data in Bioconductor containers

Functions in MLInterfaces

Name Description
fsHistory extract history of feature selection for a cross-validated machine learner
predict.classifierOutput Predict method for classifierOutput objects
planarPlot-methods Methods for Function planarPlot in Package `MLInterfaces'
xvalSpec container for information specifying a cross-validated machine learning exercise
learnerSchema-class Class "learnerSchema" -- convey information on a machine learning function to the MLearn wrapper
confuTab Compute confusion tables for a confusion matrix.
fs.absT support for feature selection in cross-validation
balKfold.xvspec generate a partition function for cross-validation, where the partitions are approximately balanced with respect to the distribution of a response variable
classifierOutput-class Class "classifierOutput"
RAB real adaboost (Friedman et al)
raboostCont-class Class "raboostCont" ~~~
MLIntInternals MLInterfaces infrastructure
performance-analytics Assessing classifier performance
xvalLoop Cross-validation in clustered computing environments
varImpStruct-class Class "varImpStruct" -- collect data on variable importance from various machine learning methods
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Details

License LGPL
LazyLoad yes
Collate AllClasses.R RAB.R pplot.R varImp.R xval.R MLearn.R MLIConverters.R MLIPredicters.R localBridge.R methods-classifierOutput.R methods-clusteringOutput.R methods-learnerSchema.R schemaInterfaces.R featSel.R partPlot.R clDesign.R plsdaI.R performance-analytics.R
biocViews Classification, Clustering

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