mlr_measures_classif.acc | R Documentation |
Measure to compare true observed labels with predicted labels in multiclass classification tasks.
The Classification Accuracy is defined as
\frac{1}{n} \sum_{i=1}^n w_i \mathbf{1} \left( t_i = r_i \right),
where w_i
are normalized weights for all observations x_i
.
This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr()
:
mlr_measures$get("classif.acc") msr("classif.acc")
Empty ParamSet
Type: "classif"
Range: [0, 1]
Minimize: FALSE
Required prediction: response
The score function calls mlr3measures::acc()
from package mlr3measures.
If the measure is undefined for the input, NaN
is returned.
This can be customized by setting the field na_value
.
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.auc
,
mlr_measures_classif.bacc
,
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.fn
,
mlr_measures_classif.fnr
,
mlr_measures_classif.fomr
,
mlr_measures_classif.fp
,
mlr_measures_classif.fpr
,
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.mauc_mu
,
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.tn
,
mlr_measures_classif.tnr
,
mlr_measures_classif.tp
,
mlr_measures_classif.tpr
Other multiclass classification measures:
mlr_measures_classif.bacc
,
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.mauc_mu
,
mlr_measures_classif.mbrier
,
mlr_measures_classif.mcc
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.