Package: Modeler 3.4.11

Kevin R. Coombes

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

Defines classes and methods to learn models and use them to predict binary outcomes. These are generic tools, but we also include specific examples for many common classifiers.

Authors:Kevin R. Coombes [aut, cre]

Modeler_3.4.11.tar.gz
Modeler_3.4.11.zip(r-4.7-any)Modeler_3.4.11.zip(r-4.6-any)
Modeler_3.4.11.tar.gz(r-4.7-any)Modeler_3.4.11.tar.gz(r-4.6-any)
Modeler_3.4.11.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
Modeler/json (API)

# Install 'Modeler' in R:

install.packages('Modeler', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

microarray clustering

3.89 score 1 packages 13 scripts 833 downloads 310 mentions 55 exports 20 dependencies

Last updated from:3c888ceacb. Checks:6 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	120
source / vignettes	OK	215
linux-release	OK	144
windows-devel	OK	81
windows-release	OK	100
wasm-release	OK	101

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

Dependencies:Biobase BiocGenerics class ClassComparison ClassDiscovery cluster Deriv e1071 generics MASS mclust neuralnet nnet oompaBase oompaData proxy randomForest Rcpp rpart TailRank

Modeler

Introduction | Simulated DataSet | Feature Selection | Fitting Models and Making Predictions

Rendered fromModeler.Rnwusingutils::Sweave

Last update: 2017-07-13
Started: 2017-07-13

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Readme and manuals

Help Manual

Help page	Topics
Feature Filtering	filterIQR filterMax filterMean filterMedian filterMin filterRange filterSD
Feature Selection	fsChisquared fsEntropy fsFisherRandomForest fsMedSplitOddsRatio fsModifiedFisher fsPearson fsSpearman fsTailRank fsTtest keepAll
Creating FittedModel objects	FittedModel
Class "FittedModel"	FittedModel-class predict,FittedModel-method
Learning models from data	learn
Fit models and make predictions with a PCA-LR classifier	learnCCP modelerCCP predictCCP
Fit models and make predictions with a KNN classifier	learnKNN modeler3NN modeler5NN predictKNN
Fit models and make predictions with a logistic regression classifier	learnLR modelerLR predictLR
Fit models and make predictions with a PCA-LR classifier	learnNNET modelerNNET predictNNET
Fit models and make predictions with a multi-level neural network classifier	learnNNET2 modelerNNET2 predictNNET2
Fit models and make predictions with a PCA-LR classifier	learnPCALR modelerPCALR predictPCALR
Fit models and make predictions with a PCA-LR classifier	learnRF modelerRF predictRF
Fit models and make predictions with a PCA-LR classifier	learnRPART modelerRPART predictRPART
Fit models and make predictions with a PCA-LR classifier	learnSelectedLR modelerSelectedLR predictSelectedLR
Fit models and make predictions with a PCA-LR classifier	learnSVM modelerSVM predictSVM
Fit models and make predictions with a PCA-LR classifier	learnTailRank modelerTailRank predictTailRank
Constructor for "Modeler" objects	Modeler
Class "Modeler"	Modeler-class

Package: Modeler 3.4.11

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

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Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)