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hybridEnsemble (version 1.7.9)

Build, Deploy and Evaluate Hybrid Ensembles

Description

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.

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Version

Install

install.packages('hybridEnsemble')

Monthly Downloads

71

Version

1.7.9

License

GPL (>= 2)

Maintainer

Last Published

March 8th, 2023

Functions in hybridEnsemble (1.7.9)

hybridEnsemble

Binary classification with Hybrid Ensemble
importance.hybridEnsemble

Importance method for hybridEnsemble objects
CVhybridEnsemble

Five times twofold cross-validation for the Hybrid Ensemble function
Credit

Credit approval (Frank and Asuncion, 2010)
predict.hybridEnsemble

Predict method for hybridEnsemble objects
plot.CVhybridEnsemble

Plot the performance of the cross-validated Hybrid Ensemble
summary.CVhybridEnsemble

Summarize the performance of the cross-validated Hybrid Ensemble
hybridEnsembleNews

Display the NEWS file