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.
|Author||Michel Ballings, Dauwe Vercamer, and Dirk Van den Poel|
|Date of publication||2015-05-30 16:22:16|
|Maintainer||Michel Ballings <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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