mlr_learners_classif.bart.Rd
Calls dbarts::bart from package dbarts.
This Learner can be instantiated via the
dictionary mlr_learners or with the associated
sugar function lrn()
:
mlr_learners$get("classif.bart") lrn("classif.bart")
Packages: dbarts
Predict Types: response, prob
Feature Types: integer, numeric, factor, ordered
Properties: twoclass, weights
ck37
mlr3::Learner
-> mlr3::LearnerClassif
-> LearnerClassifBart
new()
Creates a new instance of this R6 class.
LearnerClassifBart$new()
clone()
The objects of this class are cloneable with this method.
LearnerClassifBart$clone(deep = FALSE)
deep
Whether to make a deep clone.
# stop example failing with warning if package not installed learner = suppressWarnings(mlr3::lrn("classif.bart")) print(learner)#> <LearnerClassifBart:classif.bart> #> * Model: - #> * Parameters: list() #> * Packages: dbarts #> * Predict Type: response #> * Feature types: integer, numeric, factor, ordered #> * Properties: twoclass, weights# available parameters: learner$param_set$ids()#> [1] "ntree" "k" "power" "base" #> [5] "binaryOffset" "ndpost" "nskip" "printevery" #> [9] "keepevery" "keeptrainfits" "usequants" "numcut" #> [13] "printcutoffs" "verbose" "keepcall" "sampleronly" #> [17] "offset" "offset.test"