Measure to compare true observed labels with predicted labels in multiclass classification tasks.
This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr():
mlr_measures$get("classif.bacc")
msr("classif.bacc")
Empty ParamSet
Type: "classif"
Range: \([0, 1]\)
Minimize: FALSE
Required prediction: response
The Balanced Accuracy computes the weighted balanced accuracy, suitable for imbalanced data sets. It is defined analogously to the definition in sklearn.
First, the sample weights \(w\) are normalized per class: $$ \hat{w}_i = \frac{w_i}{\sum_j 1(y_j = y_i) w_i}. $$ The balanced accuracy is calculated as $$ \frac{1}{\sum_i \hat{w}_i} \sum_i 1(r_i = t_i) \hat{w}_i. $$
Dictionary of Measures: mlr_measures
as.data.table(mlr_measures) for a complete table of all (also dynamically created) Measure implementations.
Other classification measures:
mlr_measures_classif.acc,
mlr_measures_classif.auc,
mlr_measures_classif.bbrier,
mlr_measures_classif.ce,
mlr_measures_classif.costs,
mlr_measures_classif.dor,
mlr_measures_classif.fbeta,
mlr_measures_classif.fdr,
mlr_measures_classif.fnr,
mlr_measures_classif.fn,
mlr_measures_classif.fomr,
mlr_measures_classif.fpr,
mlr_measures_classif.fp,
mlr_measures_classif.logloss,
mlr_measures_classif.mauc_au1p,
mlr_measures_classif.mauc_au1u,
mlr_measures_classif.mauc_aunp,
mlr_measures_classif.mauc_aunu,
mlr_measures_classif.mbrier,
mlr_measures_classif.mcc,
mlr_measures_classif.npv,
mlr_measures_classif.ppv,
mlr_measures_classif.prauc,
mlr_measures_classif.precision,
mlr_measures_classif.recall,
mlr_measures_classif.sensitivity,
mlr_measures_classif.specificity,
mlr_measures_classif.tnr,
mlr_measures_classif.tn,
mlr_measures_classif.tpr,
mlr_measures_classif.tp
Other multiclass classification measures:
mlr_measures_classif.acc,
mlr_measures_classif.ce,
mlr_measures_classif.costs,
mlr_measures_classif.logloss,
mlr_measures_classif.mauc_au1p,
mlr_measures_classif.mauc_au1u,
mlr_measures_classif.mauc_aunp,
mlr_measures_classif.mauc_aunu,
mlr_measures_classif.mbrier