mlr_measures_classif.specificity {mlr3} | R Documentation |
True Negative Rate
Description
Measure to compare true observed labels with predicted labels in binary classification tasks.
Details
The True Negative Rate is defined as
Also know as "specificity".
This measure is undefined if FP + TN = 0.
Dictionary
This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr()
:
mlr_measures$get("classif.specificity") msr("classif.specificity")
Parameters
Empty ParamSet
Meta Information
Type:
"binary"
Range:
Minimize:
FALSE
Required prediction:
response
Note
The score function calls mlr3measures::specificity()
from package mlr3measures.
If the measure is undefined for the input, NaN
is returned.
This can be customized by setting the field na_value
.
See Also
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.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.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.tn
,
mlr_measures_classif.tnr
,
mlr_measures_classif.tp
,
mlr_measures_classif.tpr
Other binary classification measures:
mlr_measures_classif.auc
,
mlr_measures_classif.bbrier
,
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.npv
,
mlr_measures_classif.ppv
,
mlr_measures_classif.prauc
,
mlr_measures_classif.precision
,
mlr_measures_classif.recall
,
mlr_measures_classif.sensitivity
,
mlr_measures_classif.tn
,
mlr_measures_classif.tnr
,
mlr_measures_classif.tp
,
mlr_measures_classif.tpr