Performance Measures for Statistical Learning

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.


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

News

Reference manual

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install.packages("measures")

0.2 by Philipp Probst, 9 months ago


Browse source code at https://github.com/cran/measures


Authors: Philipp Probst [aut, cre]


Documentation:   PDF Manual  


GPL-3 license


Depends on stats

Suggests testthat


Depended on by varImp.


See at CRAN