auc()
Area Under the ROC Curve
bbrier()
Binary Brier Score
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
mcc()
Matthews Correlation Coefficient
npv()
Negative Predictive Value
ppv() precision()
ppv()
precision()
Positive Predictive Value
prauc()
Area Under the Precision-Recall Curve
tn()
True Negatives
tnr() specificity()
tnr()
specificity()
True Negative Rate
tp()
True Positives
tpr() recall() sensitivity()
tpr()
recall()
sensitivity()
True Positive Rate
acc()
Classification Accuracy
bacc()
Balanced Accuracy
ce()
Classification Error
logloss()
Log Loss
mauc_aunu() mauc_aunp() mauc_au1u() mauc_au1p()
mauc_aunu()
mauc_aunp()
mauc_au1u()
mauc_au1p()
Multiclass AUC Scores
mbrier()
Multiclass Brier Score
bias()
Bias
ktau()
Kendall's tau
mae()
Mean Absolute Errors
mape()
Mean Absolute Percent Error
maxae()
Max Absolute Error
maxse()
Max Squared Error
medae()
Median Absolute Errors
medse()
Median Squared Error
mse()
Mean Squared Error
msle()
Mean Squared Log Error
pbias()
Percent Bias
rae()
Relative Absolute Error
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
smape()
Symmetric Mean Absolute Percent Error
srho()
Spearman's rho
sse()
Sum of Squared Errors
measures
Measure Registry
confusion_matrix()
Calculate Binary Confusion Matrix
mlr3measures-package
mlr3measures: Performance Measures for 'mlr3'
