hybridEnsemble: Build, deploy and evaluate a Hybrid Ensemble

This package contains functions to build and deploy an ensemble consisting of six different sub-ensembles: Bagged Logistic Regressions, Random Forest, Stochastic AdaBoost, Kernel Factory, Bagged Neural Networks, Bagged Support Vector Machines. 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: 0.1.1
Imports: randomForest, kernelFactory, ada, rpart, ROCR, nnet, e1071, NMOF, GenSA, Rmalschains, pso, AUC, soma, genalg, reportr, nnls, quadprog, tabuSearch, glmnet
Published: 2014-03-23
Author: Michel Ballings, Dauwe Vercamer, 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_0.1.1.tar.gz
MacOS X binary: hybridEnsemble_0.1.1.tgz
Windows binary: hybridEnsemble_0.1.1.zip
Old sources: hybridEnsemble archive