hybridEnsemble: Build, Deploy and Evaluate Hybrid Ensembles

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.

AuthorMichel Ballings, Dauwe Vercamer, and Dirk Van den Poel
Date of publication2015-05-30 16:22:16
MaintainerMichel Ballings <Michel.Ballings@GMail.com>
LicenseGPL (>= 2)
Version1.0.0

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