CRAN/E | hybridEnsemble

hybridEnsemble

Build, Deploy and Evaluate Hybrid Ensembles

Installation

About

Functions to build and deploy a hybrid ensemble consisting of different sub-ensembles such as bagged logistic regressions, random forest, stochastic boosting, kernel factory, bagged neural networks, bagged support vector machines, rotation forest, bagged k-nearest neighbors, and bagged naive Bayes. Functions to cross-validate the hybrid ensemble and plot and summarize the results are also provided. There is also a function to assess the importance of the predictors.

Key Metrics

Version 1.7.9
Published 2023-03-08 407 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks hybridEnsemble results

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Maintainer

Maintainer

Michel Ballings

Michel.Ballings@GMail.com

Authors

Michel Ballings
Dauwe Vercamer
Matthias Bogaert
Dirk Van den Poel

Material

NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

hybridEnsemble archive

Imports

randomForest
kernelFactory
ada
rpart
ROCR
nnet
e1071
NMOF
GenSA
Rmalschains
pso
AUC
soma
genalg
reportr
nnls
quadprog
tabuSearch
rotationForest
FNN
glmnet
foreach
doParallel
parallel

Suggests

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