RDocumentation
Moon
Learn R
Search all packages and functions
⚠️
There's a newer version (1.1.3) of this package.
Take me there.
MLmetrics (version 1.0.0)
Machine Learning Evaluation Metrics
Description
A collection of evaluation metrics, including loss, score and utility functions, that measure regression and classification performance.
Copy Link
Copy
Link to current version
Version
Version
1.1.3
1.1.1
1.1.0
1.0.0
Down Chevron
Install
install.packages('MLmetrics')
Monthly Downloads
9,710
Version
1.0.0
License
GPL-2
Issues
8
Pull Requests
1
Stars
67
Forks
15
Repository
http://github.com/yanyachen/MLmetrics
Maintainer
Yachen Yan
Last Published
May 2nd, 2015
Functions in MLmetrics (1.0.0)
Search functions
MAE
Mean Absolute Error Loss
ConfusionMatrix
Confusion Matrix
MSE
Mean Square Error Loss
ConfusionDF
Confusion Matrix (Data Frame Format)
RMSE
Root Mean Square Error Loss
ZeroOneLoss
Normalized Zero-One Loss (Classification Error Loss)
RAE
Relative Absolute Error Loss
R2_score
R-Squared (Coefficient of Determination) Regression Score
Recall
Recall
Accuracy
Accuracy
FBeta_Score
F-Beta Score
RRSE
Root Relative Squared Error Loss
Gini
Gini Coefficient
RMSLE
Root Mean Squared Logarithmic Error Loss
Precision
Precision
F1_Score
F1 Score
MedianAE
Median Absolute Error Loss
MLmetrics
MLmetrics: Machine Learning Evaluation Metrics
MultiLogLoss
Multi Class Log Loss
AUC
Area Under the Curve (AUC)
LogLoss
Log loss/Cross-Entropy Loss