hybridEnsemble: Build, Deploy and Evaluate Hybrid Ensembles

Functions to build and deploy a hybrid ensemble consisting of different sub-ensembles such as bagged logistic regressions, random forest, stochastic boosting, kernel factory, bagged neural networks, bagged support vector machines, rotation forest, bagged k-nearest neighbors, and bagged naive Bayes. 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.

Getting started

Package details

AuthorMichel Ballings, Dauwe Vercamer, Matthias Bogaert, and Dirk Van den Poel
MaintainerMichel Ballings <Michel.Ballings@GMail.com>
LicenseGPL (>= 2)
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

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hybridEnsemble documentation built on April 1, 2023, 12:13 a.m.