Description
Performance Measures for Statistical Learning.
Description
Provides the biggest amount of statistical measures in the whole R world. Includes measures of regression, (multiclass) classification and multilabel classification. The measures come mainly from the 'mlr' package and were programed by several 'mlr' developers.
README.md
measures
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.
Installation
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. |