Calls partykit::ctree from package partykit.

Dictionary

This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn():

mlr_learners$get("classif.ctree")
lrn("classif.ctree")

Traits

  • Packages: partykit, sandwich, coin

  • Predict Types: response, prob

  • Feature Types: integer, numeric, factor, ordered

  • Properties: multiclass, twoclass, weights

References

Hothorn T, Zeileis A (2015). “partykit: A Modular Toolkit for Recursive Partytioning in R.” Journal of Machine Learning Research, 16(118), 3905-3909. http://jmlr.org/papers/v16/hothorn15a.html

Hothorn T, Hornik K, Zeileis A (2006). “Unbiased Recursive Partitioning: A Conditional Inference Framework.” Journal of Computational and Graphical Statistics, 15(3), 651–674. doi: 10.1198/106186006x133933

See also

Author

sumny

Super classes

mlr3::Learner -> mlr3::LearnerClassif -> LearnerClassifCTree

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

LearnerClassifCTree$new()


Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerClassifCTree$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

# stop example failing with warning if package not installed learner = suppressWarnings(mlr3::lrn("classif.ctree")) print(learner)
#> <LearnerClassifCTree:classif.ctree> #> * Model: - #> * Parameters: list() #> * Packages: partykit, sandwich, coin #> * Predict Type: response #> * Feature types: integer, numeric, factor, ordered #> * Properties: multiclass, twoclass, weights
# available parameters: learner$param_set$ids()
#> [1] "teststat" "splitstat" "splittest" "testtype" #> [5] "nmax" "alpha" "mincriterion" "logmincriterion" #> [9] "minsplit" "minbucket" "minprob" "stump" #> [13] "lookahead" "MIA" "nresample" "tol" #> [17] "maxsurrogate" "numsurrogate" "mtry" "maxdepth" #> [21] "multiway" "splittry" "intersplit" "majority" #> [25] "caseweights" "maxvar" "applyfun" "cores" #> [29] "saveinfo" "update" "splitflavour" "offset" #> [33] "cluster" "scores" "doFit" "maxpts" #> [37] "abseps" "releps"