Modeler: Classes and Methods for Training and Using Binary Prediction Models

The Modeler package defines classes and methods to learn models and use them to predict binary outcomes. These are generic tools, but also include specific examples for some common classifiers.

AuthorKevin R. Coombes
Bioconductor views Clustering Microarray
Date of publication2016-06-27 18:41:31
MaintainerKevin R. Coombes <krc@silicovore.com>
LicenseApache License (== 2.0)
Version3.4.0
http://oompa.r-forge.r-project.org/

View on R-Forge

Functions

filterIQR Man page
filterMax Man page
filterMean Man page
filterMedian Man page
filterMin Man page
filterRange Man page
filterSD Man page
FittedModel Man page
FittedModel-class Man page
fsChisquared Man page
fsEntropy Man page
fsFisherRandomForest Man page
fsMedSplitOddsRatio Man page
fsModifiedFisher Man page
fsPearson Man page
fsSpearman Man page
fsTailRank Man page
fsTtest Man page
keepAll Man page
learn Man page
learnCCP Man page
learnKNN Man page
learnLR Man page
learnNNET Man page
learnNNET2 Man page
learnPCALR Man page
learnRF Man page
learnRPART Man page
learnSelectedLR Man page
learnSVM Man page
learnTailRank Man page
Modeler Man page
modeler3NN Man page
modeler5NN Man page
modelerCCP Man page
Modeler-class Man page
modelerLR Man page
modelerNNET Man page
modelerNNET2 Man page
Modeler-package Man page
modelerPCALR Man page
modelerRF Man page
modelerRPART Man page
modelerSelectedLR Man page
modelerSVM Man page
modelerTailRank Man page
predictCCP Man page
predict,FittedModel-method Man page
predictKNN Man page
predictLR Man page
predictNNET Man page
predictNNET2 Man page
predictPCALR Man page
predictRF Man page
predictRPART Man page
predictSelectedLR Man page
predictSVM Man page
predictTailRank Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.