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MLmetrics  

Machine Learning Evaluation Metrics
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("MLmetrics", "1.1.3")



Attach the package and use:
library("MLmetrics")
Maintained by
Yachen Yan
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-05-02
Latest Update: 2024-04-13
Description:
A collection of evaluation metrics, including loss, score and utility functions, that measure regression, classification and ranking performance.
How to cite:
Yachen Yan (2015). MLmetrics: Machine Learning Evaluation Metrics. R package version 1.1.3, https://cran.r-project.org/web/packages/MLmetrics. Accessed 07 Mar. 2026.
Previous versions and publish date:
1.0.0 (2015-05-02 09:26), 1.1.0 (2016-05-01 18:32), 1.1.1 (2016-05-13 23:57)
Other packages that cited MLmetrics R package
View MLmetrics citation profile
Other R packages that MLmetrics depends, imports, suggests or enhances
Complete documentation for MLmetrics
Functions, R codes and Examples using the MLmetrics R package
Some associated functions: AUC . Accuracy . Area_Under_Curve . ConfusionDF . ConfusionMatrix . F1_Score . FBeta_Score . GainAUC . Gini . KS_Stat . LiftAUC . LogLoss . MAE . MAPE . MLmetrics . MSE . MedianAE . MedianAPE . MultiLogLoss . NormalizedGini . PRAUC . Poisson_LogLoss . Precision . R2_Score . RAE . RMSE . RMSLE . RMSPE . RRSE . Recall . Sensitivity . Specificity . ZeroOneLoss . 
Some associated R codes: Classification.R . Count.R . MLmetrics.R . Rank.R . Regression.R . Utils.R .  Full MLmetrics package functions and examples
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