Functions to build and deploy a hybrid ensemble consisting of eight different sub-ensembles: bagged logistic regressions, random forest, stochastic boosting, kernel factory, bagged neural networks, bagged support vector machines, rotation forest, and bagged k-nearest neighbors. 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: |
1.0.0 |
| Imports: |
randomForest, kernelFactory, ada, rpart, ROCR, nnet, e1071, NMOF, GenSA, Rmalschains, pso, AUC, soma, genalg, reportr, nnls, quadprog, tabuSearch, rotationForest, FNN, glmnet |
| Suggests: |
testthat |
| Published: |
2015-05-30 |
| Author: |
Michel Ballings, Dauwe Vercamer, and Dirk Van den Poel |
| Maintainer: |
Michel Ballings <Michel.Ballings at GMail.com> |
| BugReports: |
NA |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
NA |
| NeedsCompilation: |
no |
| Materials: |
NEWS |
| CRAN checks: |
hybridEnsemble results |