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ConfusionTableR  

Confusion Matrix Toolset
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("ConfusionTableR", "1.0.4")



Attach the package and use:
library("ConfusionTableR")
Maintained by
Gary Hutson
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-07-21
Latest Update: 2021-12-01
Description:
Takes the outputs of a 'caret' confusion matrix and allows for the quick conversion of these list items to lists. The intended usage is to allow the tool to work with the outputs of machine learning classification models. This tool works with classification problems for binary and multi-classification problems and allows for the record level conversion of the confusion matrix outputs. This is useful, as it allows quick conversion of these objects for storage in database systems and to track ML model performance over time. Traditionally, this approach has been used for highlighting model representation and feature slippage.
How to cite:
Gary Hutson (2021). ConfusionTableR: Confusion Matrix Toolset. R package version 1.0.4, https://cran.r-project.org/web/packages/ConfusionTableR. Accessed 07 Aug. 2026.
Previous versions and publish date:
1.0.1 (2021-07-21 11:50), 1.0.2 (2021-10-07 22:40), 1.0.3 (2021-11-01 16:20), (2026-07-09 08:00)
Other packages that cited ConfusionTableR R package
View ConfusionTableR citation profile
Other R packages that ConfusionTableR depends, imports, suggests or enhances
Complete documentation for ConfusionTableR
Functions, R codes and Examples using the ConfusionTableR R package
Some associated functions: binary_class_cm . binary_visualiseR . dummy_encoder . multi_class_cm . 
Some associated R codes: MultiFramer.R . SingleFramer.R . binaryVisualiseR.R . dummycoder.R . globals.R .  Full ConfusionTableR package functions and examples
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