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LogisticEnsembles  

Automatically Runs 36 Logistic Models (Individual and Ensembles)
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("LogisticEnsembles", "0.5.0")



Attach the package and use:
library("LogisticEnsembles")
Maintained by
Russ Conte
[Scholar Profile | Author Map]
First Published: 2025-04-01
Latest Update: 2025-04-01
Description:
Automatically returns 36 logistic models including 23 individual models and 13 ensembles of models of logistic data. The package also returns 10 plots, 5 tables, and a summary report. The package automatically builds all 36 models, reports all results, and provides graphics to show how the models performed. This can be used for a wide range of data sets. The package includes medical data (the Pima Indians data set), and information about the performance of Lebron James. The package can be used to analyze many other examples, such as stock market data. The package automatically returns many values for each model, such as True Positive Rate, True Negative Rate, False Positive Rate, False Negative Rate, Positive Predictive Value, Negative Predictive Value, F1 Score, Area Under the Curve. The package also returns 36 Receiver Operating Characteristic (ROC) curves for each of the 36 models.
How to cite:
Russ Conte (2025). LogisticEnsembles: Automatically Runs 36 Logistic Models (Individual and Ensembles). R package version 0.5.0, https://cran.r-project.org/web/packages/LogisticEnsembles. Accessed 05 May. 2025.
Previous versions and publish date:
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Complete documentation for LogisticEnsembles
Functions, R codes and Examples using the LogisticEnsembles R package
Full LogisticEnsembles package functions and examples
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