hybridEnsemble: Build, Deploy and Evaluate Hybrid Ensembles

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.

Version: 1.7.9
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: testthat
Published: 2023-03-08
Author: Michel Ballings, Dauwe Vercamer, Matthias Bogaert, and Dirk Van den Poel
Maintainer: Michel Ballings <Michel.Ballings at GMail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: NEWS
CRAN checks: hybridEnsemble results


Reference manual: hybridEnsemble.pdf


Package source: hybridEnsemble_1.7.9.tar.gz
Windows binaries: r-devel: hybridEnsemble_1.7.9.zip, r-release: hybridEnsemble_1.7.9.zip, r-oldrel: hybridEnsemble_1.7.9.zip
macOS binaries: r-release (arm64): hybridEnsemble_1.7.9.tgz, r-oldrel (arm64): hybridEnsemble_1.7.9.tgz, r-release (x86_64): hybridEnsemble_1.7.9.tgz, r-oldrel (x86_64): hybridEnsemble_1.7.9.tgz
Old sources: hybridEnsemble archive


Please use the canonical form https://CRAN.R-project.org/package=hybridEnsemble to link to this page.