Description Super classes Methods References
Random forest learner. randomForest from package randomForest.
mlr3::Learner
-> mlr3::LearnerClassif
-> LearnerClassifRandomForest
new()
Creates a new instance of this R6 class.
LearnerClassifRandomForest$new()
importance()
The importance scores are extracted from the slot importance
.
Parameter 'importance' must be set to either "accuracy"
or "gini"
.
LearnerClassifRandomForest$importance()
Named numeric()
.
oob_error()
OOB errors are extracted from the model slot err.rate
.
LearnerClassifRandomForest$oob_error()
numeric(1)
.
clone()
The objects of this class are cloneable with this method.
LearnerClassifRandomForest$clone(deep = FALSE)
deep
Whether to make a deep clone.
Breiman, L. (2001). Random Forests Machine Learning https://doi.org/10.1023/A:1010933404324
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