R: Performance Measures for Statistical Learning

# Performance Measures for Statistical Learning

## Documentation for package ‘measures’ version 0.3

- DESCRIPTION file
- Package README

## Help Pages

ACC | Accuracy
ARSQ | Adjusted coefficient of determination
AUC | Area under the curve
BAC | Balanced accuracy
BER | Balanced error rate
Brier | Brier score
BrierScaled | Brier scaled
EXPVAR | Explained variance
F1 | F1 measure
FDR | False discovery rate
FN | False negatives
FNR | False negative rate
FP | False positives
FPR | False positive rate
GMEAN | G-mean
GPR | Geometric mean of precision and recall.
KAPPA | Cohen's kappa
KendallTau | Kendall's tau
listAllMeasures | List all measures
Logloss | Logarithmic loss
LSR | Logarithmic Scoring Rule
MAE | Mean of absolute errors
MAPE | Mean absolute percentage error
MCC | Matthews correlation coefficient
MEDAE | Median of absolute errors
MEDSE | Median of squared errors
MMCE | Mean misclassification error
MSE | Mean of squared errors
MSLE | Mean squared logarithmic error
multiclass.AU1P | Weighted average 1 vs. 1 multiclass AUC
multiclass.AU1U | Average 1 vs. 1 multiclass AUC
multiclass.AUNP | Weighted average 1 vs. rest multiclass AUC
multiclass.AUNU | Average 1 vs. rest multiclass AUC
multiclass.Brier | Multiclass Brier score
MultilabelACC | Accuracy (multilabel)
MultilabelF1 | F1 measure (multilabel)
MultilabelHamloss | Hamming loss
MultilabelPPV | Positive predictive value (multilabel)
MultilabelSubset01 | Subset-0-1 loss
MultilabelTPR | TPR (multilabel)
NPV | Negative predictive value
PPV | Positive predictive value
QSR | Quadratic Scoring Rule
RAE | Relative absolute error
RMSE | Root mean squared error
RMSLE | Root mean squared logarithmic error
RRSE | Root relative squared error
RSQ | Coefficient of determination
SAE | Sum of absolute errors
SpearmanRho | Spearman's rho
SSE | Sum of squared errors
SSR | Spherical Scoring Rule
TN | True negatives
TNR | True negative rate
TP | True positives
TPR | True positive rate
WKAPPA | Mean quadratic weighted kappa