MLmetrics-package |
MLmetrics: Machine Learning Evaluation Metrics |
Accuracy |
Accuracy |
Area_Under_Curve |
Calculate the Area Under the Curve |
AUC |
Area Under the Receiver Operating Characteristic Curve (ROC AUC) |
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) |