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.

Documentation

Manual: hybridEnsemble.pdf
Vignette: None available.

Maintainer: Michel Ballings <Michel.Ballings at GMail.com>

Author(s): Michel Ballings, Dauwe Vercamer, and Dirk Van den Poel

Install package and any missing dependencies by running this line in your R console:

install.packages("hybridEnsemble")

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Package hybridEnsemble
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Version 1.0.0
Published 2015-05-30
License GPL (>= 2)
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NeedsCompilation no
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CRAN checks hybridEnsemble check results
Package source hybridEnsemble_1.0.0.tar.gz