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autoEnsemble
View on CRAN: Click
here
Download and install autoEnsemble package within the R console
Install from CRAN:
install.packages("autoEnsemble")
Install from Github:
library("remotes")
install_github("cran/autoEnsemble")
Install by package version:
library("remotes")
install_version("autoEnsemble", "0.2")
Attach the package and use:
library("autoEnsemble")
Maintained by
E. F. Haghish
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.autoEnsemble . https://github.com/haghish/autoEnsemble/issues . https://github.com/haghish/autoEnsemble . autoEnsemble results . autoEnsemble.pdf . autoEnsemble_0.3.tar.gz . autoEnsemble_0.3.zip . autoEnsemble_0.3.zip . autoEnsemble_0.3.zip . autoEnsemble_0.3.tgz . autoEnsemble_0.3.tgz . autoEnsemble_0.3.tgz . autoEnsemble_0.3.tgz . autoEnsemble_0.3.tgz . autoEnsemble_0.3.tgz . autoEnsemble archive . https://CRAN.R-project.org/package=autoEnsemble .
First Published: 2023-05-09
Latest Update: 2023-05-09
Description:
An AutoML algorithm is developed to construct homogeneous or
heterogeneous stacked ensemble models using specified base-learners.
Various criteria are employed to identify optimal models, enhancing
diversity among them and resulting in more robust stacked ensembles.
The algorithm optimizes the model by incorporating an increasing
number of top-performing models to create a diverse combination.
Presently, only models from 'h2o.ai' are supported.
How to cite:
E. F. Haghish (2023). autoEnsemble: Automated Stacked Ensemble Classifier for Severe Class Imbalance. R package version 0.2, https://cran.r-project.org/web/packages/autoEnsemble. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.2 (2023-05-09 11:30)
Other packages that cited autoEnsemble R package
View autoEnsemble citation profile
Other R packages that autoEnsemble depends,
imports, suggests or enhances
Complete documentation for autoEnsemble
Functions, R codes and Examples using
the autoEnsemble R package
Some associated functions: ensemble . evaluate . h2o.get_ids . modelSelection . stopping_criteria .
Some associated R codes: ensemble.R . evaluate.R . h2o.get_ids.R . modelSelection.R . stopping_criteria.R . Full autoEnsemble package functions and examples
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