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hybridEnsemble
View on CRAN: Click
here
Download and install hybridEnsemble package within the R console
Install from CRAN:
install.packages("hybridEnsemble")
Install from Github:
library("remotes")
install_github("cran/hybridEnsemble")
Install by package version:
library("remotes")
install_version("hybridEnsemble", "1.7.9")
Attach the package and use:
library("hybridEnsemble")
Maintained by
Michel Ballings
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2013-12-19
Latest Update: 2023-04-03
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.
How to cite:
Michel Ballings (2013). hybridEnsemble: Build, Deploy and Evaluate Hybrid Ensembles. R package version 1.7.9, https://cran.r-project.org/web/packages/hybridEnsemble
Previous versions and publish date:
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imports, suggests or enhances
Functions, R codes and Examples using
the hybridEnsemble R package
Some associated functions: CVhybridEnsemble . Credit . hybridEnsemble . hybridEnsembleNews . importance.hybridEnsemble . plot.CVhybridEnsemble . predict.hybridEnsemble . summary.CVhybridEnsemble .
Some associated R codes: CVhybridEnsemble.R . auxiliary.R . hybridEnsemble.R . hybridEnsembleNews.R . importance.hybridEnsemble.R . plot.CVhybridEnsemble.R . predict.hybridEnsemble.R . summary.CVhybridEnsemble.R . zzz.R . Full hybridEnsemble package functions and examples
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