mlr_measures_oob_error | R Documentation |
Returns the out-of-bag error of the Learner for learners that support it
(learners with property "oob_error"
).
Returns NA
for unsupported learners.
This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr()
:
mlr_measures$get("oob_error") msr("oob_error")
Task type: “NA”
Range: (-\infty, \infty)
Minimize: TRUE
Average: macro
Required Prediction: “NA”
Required Packages: mlr3
Empty ParamSet
mlr3::Measure
-> MeasureOOBError
new()
Creates a new instance of this R6 class.
MeasureOOBError$new()
clone()
The objects of this class are cloneable with this method.
MeasureOOBError$clone(deep = FALSE)
deep
Whether to make a deep clone.
Chapter in the mlr3book: https://mlr3book.mlr-org.com/chapters/chapter2/data_and_basic_modeling.html#sec-eval
Package mlr3measures for the scoring functions.
Dictionary of Measures: mlr_measures
as.data.table(mlr_measures)
for a table of available Measures in the running session (depending on the loaded packages).
Extension packages for additional task types:
mlr3proba for probabilistic supervised regression and survival analysis.
mlr3cluster for unsupervised clustering.
Other Measure:
Measure
,
MeasureClassif
,
MeasureRegr
,
MeasureSimilarity
,
mlr_measures
,
mlr_measures_aic
,
mlr_measures_bic
,
mlr_measures_classif.costs
,
mlr_measures_debug_classif
,
mlr_measures_elapsed_time
,
mlr_measures_internal_valid_score
,
mlr_measures_regr.rsq
,
mlr_measures_selected_features
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