Binary Classification Measures

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()

Positive Predictive Value

tn()

True Negatives

tnr() specificity()

True Negative Rate

tp()

True Positives

tpr() recall() sensitivity()

True Positive Rate

Classification Measures

acc()

Classification Accuracy

bacc()

Balanced Accuracy

ce()

Classification Error

logloss()

Log Loss

mauc_aunu() mauc_aunp() mauc_au1u() mauc_au1p()

Multiclass AUC Scores

mbrier()

Multiclass Brier Score

Regression Measures

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

Misc

measures

Measure Registry

confusion_matrix()

Calculate Binary Confusion Matrix

mlr3measures-package

mlr3measures: Performance Measures for 'mlr3'