Measure Internal Validation Score
Source:R/MeasureInternalValidScore.R
mlr_measures_internal_valid_score.Rd
Returns the selected internal validation score of the Learner for learners property "validation"
.
Returns NA
for unsupported learners, when no validation was done, or when the selected id was not found.
Parameters
select
: (character(1)
)
Which of the internal validation scores to select. Which scores are available depends on the learner. By default, the first score is chosen.
Id | Type | Default |
select | untyped | - |
Dictionary
This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr()
:
Meta Information
Task type: “NA”
Range: \((-\infty, \infty)\)
Minimize: NA
Average: macro
Required Prediction: “NA”
Required Packages: mlr3
See also
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_oob_error
,
mlr_measures_selected_features
Super class
mlr3::Measure
-> MeasureInternalValidScore
Examples
rr = resample(tsk("iris"), lrn("classif.debug", validate = 0.3), rsmp("holdout"))
rr$score(msr("internal_valid_score", select = "acc"))
#> task_id learner_id resampling_id iteration internal_valid_score
#> <char> <char> <char> <int> <num>
#> 1: iris classif.debug holdout 1 0.3
#> Hidden columns: task, learner, resampling, prediction