Performance Measures for Statistical Learning

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Documentation for package ‘measures’ version 0.3

• DESCRIPTION file.

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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