# Performance Measures for 'mlr3'

## Documentation for package ‘mlr3measures’ version 1.3.0

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

mlr3measures-package | 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
ce | Classification Error
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
gmean | Geometric Mean of Recall and Specificity
gpr | Geometric Mean of Precision and Recall
jaccard | Jaccard Similarity Index
ktau | Kendall's tau
linex | Linear-Exponential Loss (per observation)
logloss | Log Loss
mae | Mean Absolute Error
mape | Mean Absolute Percent Error
mauc_au1p | Multiclass AUC Scores
mauc_au1u | Multiclass AUC Scores
mauc_aunp | Multiclass AUC Scores
mauc_aunu | Multiclass AUC Scores
mauc_mu | 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 | mlr3measures: Performance Measures for 'mlr3'
mse | Mean Squared Error
msle | Mean Squared Log Error
npv | Negative Predictive Value
one_zero | Zero-One Classification Loss (per observation)
pbias | Percent Bias
phi | Phi Coefficient Similarity
pinball | Average Pinball Loss
ppv | Positive Predictive Value
prauc | Area Under the Precision-Recall Curve
precision | Positive Predictive Value
rae | Relative Absolute Error
recall | True Positive Rate
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)
sensitivity | True Positive Rate
sle | Squared Log Error (per observation)
smape | Symmetric Mean Absolute Percent Error
specificity | True Negative Rate
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)