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IRon  

Solving Imbalanced Regression Tasks
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("IRon", "0.1.5")



Attach the package and use:
library("IRon")
Maintained by
Nuno Moniz
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-05-27
Latest Update: 2023-01-20
Description:
Imbalanced domain learning has almost exclusively focused on solving classification tasks, where the objective is to predict cases labelled with a rare class accurately. Such a well-defined approach for regression tasks lacked due to two main factors. First, standard regression tasks assume that each value is equally important to the user. Second, standard evaluation metrics focus on assessing the performance of the model on the most common cases. This package contains methods to tackle imbalanced domain learning problems in regression tasks, where the objective is to predict extreme (rare) values. The methods contained in this package are: 1) an automatic and non-parametric method to obtain such relevance functions; 2) visualisation tools; 3) suite of evaluation measures for optimisation/validation processes; 4) the squared-error relevance area measure, an evaluation metric tailored for imbalanced regression tasks. More information can be found in Ribeiro and Moniz (2020) .
How to cite:
Nuno Moniz (2022). IRon: Solving Imbalanced Regression Tasks. R package version 0.1.5, https://cran.r-project.org/web/packages/IRon. Accessed 05 Mar. 2026.
Previous versions and publish date:
0.1.0 (2022-05-27 10:00), 0.1.2 (2022-06-14 08:50), 0.1.3 (2022-10-29 01:32), 0.1.4 (2023-01-20 08:20)
Other packages that cited IRon R package
View IRon citation profile
Other R packages that IRon depends, imports, suggests or enhances
Complete documentation for IRon
Functions, R codes and Examples using the IRon R package
Some associated functions: NO2Emissions . accel . bias . corr . eval.stats . mae . mse . phi.control . phi.extremes . phi . phi.range . phiPlot . rmse . ser . sera . variance . 
Some associated R codes: data.R . evalStats.R . nonstdMetrics.R . phi.R . phi_plot.R . stdMetrics.R .  Full IRon package functions and examples
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