Man pages for mlr3measures
Performance Measures for 'mlr3'

acc	Classification Accuracy
ae	Absolute Error (per observation)
ape	Absolute Percentage Error (per observation)
auc	Area Under the ROC Curve
bacc	Balanced Accuracy
bbrier	Binary Brier Score
bias	Bias
binary_params	Binary Classification Parameters
ce	Classification Error
classif_params	Classification Parameters
confusion_matrix	Calculate Binary Confusion Matrix
dor	Diagnostic Odds Ratio
fbeta	F-beta Score
fdr	False Discovery Rate
fn	False Negatives
fnr	False Negative Rate
fomr	False Omission Rate
fp	False Positives
fpr	False Positive Rate
jaccard	Jaccard Similarity Index
ktau	Kendall's tau
logloss	Log Loss
mae	Mean Absolute Error
mape	Mean Absolute Percent Error
mauc_aunu	Multiclass AUC Scores
maxae	Max Absolute Error
maxse	Max Squared Error
mbrier	Multiclass Brier Score
mcc	Matthews Correlation Coefficient
measures	Measure Registry
medae	Median Absolute Error
medse	Median Squared Error
mlr3measures-package	mlr3measures: Performance Measures for 'mlr3'
mse	Mean Squared Error
msle	Mean Squared Log Error
npv	Negative Predictive Value
pbias	Percent Bias
phi	Phi Coefficient Similarity
ppv	Positive Predictive Value
prauc	Area Under the Precision-Recall Curve
rae	Relative Absolute Error
regr_params	Regression Parameters
rmse	Root Mean Squared Error
rmsle	Root Mean Squared Log Error
rrse	Root Relative Squared Error
rse	Relative Squared Error
rsq	R Squared
sae	Sum of Absolute Errors
se	Squared Error (per observation)
similarity_params	Similarity Parameters
sle	Squared Log Error (per observation)
smape	Symmetric Mean Absolute Percent Error
srho	Spearman's rho
sse	Sum of Squared Errors
tn	True Negatives
tnr	True Negative Rate
tp	True Positives
tpr	True Positive Rate
zero_one	Zero-One Classification Loss (per observation)