Log Loss
Measure to compare true observed labels with predicted probabilities in multiclass classification tasks.
The Log Loss (a.k.a Benoulli Loss, Logistic Loss, Cross-Entropy Loss) is defined as
where is the probability for the true class of observation and are normalized weights for each observation .
The score function calls mlr3measures::logloss()
from package list("mlr3measures").
If the measure is undefined for the input, NaN
is returned. This can be customized by setting the field na_value
.
This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr()
:
mlr_measures$get("classif.logloss")
msr("classif.logloss")
Empty ParamSet
"classif"
TRUE
prob
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.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.acc
, mlr_measures_classif.bacc
, mlr_measures_classif.ce
, mlr_measures_classif.costs
, 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
Useful links