Selected Features Measure
Measures the number of selected features by extracting it from learners with property "selected_features".
If the learner does not support this, NA is returned.
This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr():
mlr_measures$get("selected_features")
msr("selected_features") Type: NA
Range: [0, Inf)
Minimize: TRUE
Required prediction: 'response'
mlr3::Measure -> MeasureSelectedFeatures
normalize(logical(1))
If set to TRUE, divides the number of features by the total number of features.
new()
Creates a new instance of this R6 class.
MeasureSelectedFeatures$new(normalize = FALSE)
normalize(logical(1))
If set to TRUE, divides the number of features by the total number of features.
clone()
The objects of this class are cloneable with this method.
MeasureSelectedFeatures$clone(deep = FALSE)
deepWhether to make a deep clone.
as.data.table(mlr_measures) for a complete table of all (also dynamically created) Measure implementations.
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