https://github.com/pat-s/measures
https://github.com/pat-s/measures
Last synced: about 2 months ago
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- Host: GitHub
- URL: https://github.com/pat-s/measures
- Owner: pat-s
- Created: 2018-02-13T15:28:06.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-07-19T17:56:39.000Z (almost 7 years ago)
- Last Synced: 2025-02-28T21:47:31.005Z (3 months ago)
- Language: R
- Size: 55.7 KB
- Stars: 5
- Watchers: 12
- Forks: 2
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
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README
# 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](https://github.com/mlr-org/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 |