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MLInterfaces (version 1.52.0)

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

Description

This package provides uniform interfaces to machine learning code for data in R and Bioconductor containers.

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Version

Version

1.52.0

License

LGPL

Maintainer

Vince Carey

Last Published

February 15th, 2017

Functions in MLInterfaces (1.52.0)

MLIntInternals

MLInterfaces infrastructure
confuTab

Compute confusion tables for a confusion matrix.
learnerSchema-class

Class "learnerSchema" -- convey information on a machine learning function to the MLearn wrapper
hclustWidget

shiny-oriented GUI for cluster or classifier exploration
fs.absT

support for feature selection in cross-validation
clusteringOutput-class

container for clustering outputs in uniform structure
confuMat-methods

Compute the confusion matrix for a classifier.
projectedLearner-class

Class "projectedLearner"
fsHistory

extract history of feature selection for a cross-validated machine learner
performance-analytics

Assessing classifier performance
varImpStruct-class

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

real adaboost (Friedman et al)
xvalSpec

container for information specifying a cross-validated machine learning exercise
balKfold.xvspec

generate a partition function for cross-validation, where the partitions are approximately balanced with respect to the distribution of a response variable
projectLearnerToGrid

create learned tesselation of feature space after PC transformation
plspinHcube

shiny app for interactive 3D visualization of mlbench hypercube
MLearn

revised MLearn interface for machine learning
planarPlot-methods

Methods for Function planarPlot in Package `MLInterfaces'
predict.classifierOutput

Predict method for classifierOutput objects
raboostCont-class

Class "raboostCont" ~~~
classifierOutput-class

Class "classifierOutput"
xvalLoop

Cross-validation in clustered computing environments