MLmetrics: Machine Learning Evaluation Metrics
Version 1.1.1

A collection of evaluation metrics, including loss, score and utility functions, that measure regression, classification and ranking performance.

Browse man pages Browse package API and functions Browse package files

AuthorYachen Yan [aut, cre]
Date of publication2016-05-13 23:57:26
MaintainerYachen Yan <yanyachen21@gmail.com>
LicenseGPL-2
Version1.1.1
URL http://github.com/yanyachen/MLmetrics
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("MLmetrics")

Man pages

Accuracy: Accuracy
Area_Under_Curve: Calculate the Area Under the Curve
AUC: Area Under the Receiver Operating Characteristic Curve (ROC...
ConfusionDF: Confusion Matrix (Data Frame Format)
ConfusionMatrix: Confusion Matrix
F1_Score: F1 Score
FBeta_Score: F-Beta Score
GainAUC: Area Under the Gain Chart
Gini: Gini Coefficient
KS_Stat: Kolmogorov-Smirnov Statistic
LiftAUC: Area Under the Lift Chart
LogLoss: Log loss / Cross-Entropy Loss
MAE: Mean Absolute Error Loss
MAPE: Mean Absolute Percentage Error Loss
MedianAE: Median Absolute Error Loss
MedianAPE: Median Absolute Percentage Error Loss
MLmetrics: MLmetrics: Machine Learning Evaluation Metrics
MSE: Mean Square Error Loss
MultiLogLoss: Multi Class Log Loss
NormalizedGini: Normalized Gini Coefficient
Poisson_LogLoss: Poisson Log loss
PRAUC: Area Under the Precision-Recall Curve (PR AUC)
Precision: Precision
R2_Score: R-Squared (Coefficient of Determination) Regression Score
RAE: Relative Absolute Error Loss
Recall: Recall
RMSE: Root Mean Square Error Loss
RMSLE: Root Mean Squared Logarithmic Error Loss
RMSPE: Root Mean Square Percentage Error Loss
RRSE: Root Relative Squared Error Loss
Sensitivity: Sensitivity
Specificity: Specificity
ZeroOneLoss: Normalized Zero-One Loss (Classification Error Loss)

Functions

AUC Man page Source code
Accuracy Man page Source code
Area_Under_Curve Man page Source code
ConfusionDF Man page Source code
ConfusionMatrix Man page Source code
F1_Score Man page Source code
FBeta_Score Man page Source code
GainAUC Man page Source code
Gini Man page Source code
KS_Stat Man page Source code
LiftAUC Man page Source code
LogLoss Man page Source code
MAE Man page Source code
MAPE Man page Source code
MLmetrics Man page
MLmetrics-package Man page
MSE Man page Source code
MedianAE Man page Source code
MedianAPE Man page Source code
MultiLogLoss Man page Source code
NormalizedGini Man page Source code
PRAUC Man page Source code
Poisson_LogLoss Man page Source code
Precision Man page Source code
R2_Score Man page Source code
RAE Man page Source code
RMSE Man page Source code
RMSLE Man page Source code
RMSPE Man page Source code
RRSE Man page Source code
Recall Man page Source code
Sensitivity Man page Source code
Specificity Man page Source code
ZeroOneLoss Man page Source code

Files

NAMESPACE
R
R/Utils.R
R/Count.R
R/Regression.R
R/MLmetrics.R
R/Rank.R
R/Classification.R
MD5
DESCRIPTION
man
man/MSE.Rd
man/LiftAUC.Rd
man/MultiLogLoss.Rd
man/MLmetrics.Rd
man/NormalizedGini.Rd
man/MedianAE.Rd
man/GainAUC.Rd
man/PRAUC.Rd
man/Poisson_LogLoss.Rd
man/ZeroOneLoss.Rd
man/AUC.Rd
man/Sensitivity.Rd
man/Accuracy.Rd
man/RMSPE.Rd
man/Recall.Rd
man/MedianAPE.Rd
man/MAPE.Rd
man/FBeta_Score.Rd
man/ConfusionDF.Rd
man/R2_Score.Rd
man/LogLoss.Rd
man/Precision.Rd
man/ConfusionMatrix.Rd
man/Area_Under_Curve.Rd
man/RRSE.Rd
man/KS_Stat.Rd
man/MAE.Rd
man/RMSLE.Rd
man/RAE.Rd
man/Gini.Rd
man/F1_Score.Rd
man/Specificity.Rd
man/RMSE.Rd
MLmetrics documentation built on May 20, 2017, 12:52 a.m.