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ClassificationEnsembles  

Automatically Builds 12 Classification Models
View on CRAN: Click here


Download and install ClassificationEnsembles package within the R console
Install from CRAN:
install.packages("ClassificationEnsembles")

Install from Github:
library("remotes")
install_github("cran/ClassificationEnsembles")

Install by package version:
library("remotes")
install_version("ClassificationEnsembles", "0.7.1")



Attach the package and use:
library("ClassificationEnsembles")
Maintained by
Russ Conte
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-04-01
Latest Update: 2025-07-31
Description:
Automatically builds 20 classification models from data. The package returns 26 plots, 5 tables and a summary report. The package automatically builds 12 individual classification models, including error (RMSE) and predictions. That data is used to create an ensemble, which is then modeled using 8 methods. The process is repeated as many times as the user requests. The mean of the results are presented in a summary table. The package returns the confusion matrices for all 20 models, tables of the correlation of the numeric data, the results of the variance inflation process, the head of the ensemble and the head of the data frame.
How to cite:
Russ Conte (2025). ClassificationEnsembles: Automatically Builds 12 Classification Models. R package version 0.7.1, https://cran.r-project.org/web/packages/ClassificationEnsembles. Accessed 05 Jun. 2026.
Previous versions and publish date:
0.5.0 (2025-04-01 18:10), 0.6.0 (2025-08-01 00:02), 0.7.0 (2025-10-13 00:50), 0.7.1 (2025-10-15 17:30), 1.0.0 (2026-02-15 20:50)
Other packages that cited ClassificationEnsembles R package
View ClassificationEnsembles citation profile
Other R packages that ClassificationEnsembles depends, imports, suggests or enhances
Complete documentation for ClassificationEnsembles
Functions, R codes and Examples using the ClassificationEnsembles R package
Full ClassificationEnsembles package functions and examples
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