Package that provides the biggest amount of statistical measures in the whole R world!
Includes measures of regression, (multiclass) classification, clustering, survival and multilabel classification.
It is based on measures of mlr.
The development version
devtools::install_github("mlr-org/measures")
The available measures can be looked up by
listAllMeasures()
|function_name |description |task | |:------------------|:------------------------------------------|:-------------------------| |SSE |Sum of squared errors |regression | |MSE |Mean of squared errors |regression | |RMSE |Root mean squared error |regression | |MEDSE |Median of squared errors |regression | |SAE |Sum of absolute errors |regression | |MAE |Mean of absolute errors |regression | |MEDAE |Median of absolute errors |regression | |RSQ |Coefficient of determination |regression | |EXPVAR |Explained variance |regression | |ARSQ |Adjusted coefficient of determination |regression | |RRSE |Root relative squared error |regression | |RAE |Relative absolute error |regression | |MAPE |Mean absolute percentage error |regression | |MSLE |Mean squared logarithmic error |regression | |RMSLE |Root mean squared logarithmic error |regression | |KendallTau |Kendall's tau |regression | |SpearmanRho |Spearman's rho |regression | |AUC |Area under the curve |binary classification | |Brier |Brier score |binary classification | |BrierScaled |Brier scaled |binary classification | |BAC |Balanced accuracy |binary classification | |TP |True positives |binary classification | |TN |True negatives |binary classification | |FP |False positives |binary classification | |FN |False negatives |binary classification | |TPR |True positive rate |binary classification | |TNR |True negative rate |binary classification | |FPR |False positive rate |binary classification | |FNR |False negative rate |binary classification | |PPV |Positive predictive value |binary classification | |NPV |Negative predictive value |binary classification | |FDR |False discovery rate |binary classification | |MCC |Matthews correlation coefficient |binary classification | |F1 |F1 measure |binary classification | |GMEAN |G-mean |binary classification | |GPR |Geometric mean of precision and recall. |binary classification | |MMCE |Mean misclassification error |multiclass classification | |ACC |Accuracy |multiclass classification | |BER |Balanced error rate |multiclass classification | |multiclass.AUNU |Average 1 vs. rest multiclass AUC |multiclass classification | |multiclass.AUNP |Weighted average 1 vs. rest multiclass AUC |multiclass classification | |multiclass.AU1U |Average 1 vs. 1 multiclass AUC |multiclass classification | |multiclass.AU1P |Weighted average 1 vs. 1 multiclass AUC |multiclass classification | |multiclass.Brier |Multiclass Brier score |multiclass classification | |Logloss |Logarithmic loss |multiclass classification | |SSR |Spherical Scoring Rule |multiclass classification | |QSR |Quadratic Scoring Rule |multiclass classification | |LSR |Logarithmic Scoring Rule |multiclass classification | |KAPPA |Cohen's kappa |multiclass classification | |WKAPPA |Mean quadratic weighted kappa |multiclass classification | |MultilabelHamloss |Hamming loss |multilabel | |MultilabelSubset01 |Subset-0-1 loss |multilabel | |MultilabelF1 |F1 measure (multilabel) |multilabel | |MultilabelACC |Accuracy (multilabel) |multilabel | |MultilabelPPV |Positive predictive value (multilabel) |multilabel | |MultilabelTPR |TPR (multilabel) |multilabel |
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