Calls partykit::mob 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.mob")
lrn("classif.mob")

Traits

  • Packages: partykit, sandwich, coin

  • Predict Types: response, prob

  • Feature Types: logical, integer, numeric, character, 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

Zeileis A, Hothorn T, Hornik K (2008). “Model-Based Recursive Partitioning.” Journal of Computational and Graphical Statistics, 17(2), 492–514. doi: 10.1198/106186008X319331

See also

Author

sumny

Super classes

mlr3::Learner -> mlr3::LearnerClassif -> LearnerClassifMob

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

LearnerClassifMob$new()


Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerClassifMob$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.mob")) print(learner)
#> <LearnerClassifMob:classif.mob> #> * Model: - #> * Parameters: list() #> * Packages: partykit, sandwich, coin #> * Predict Type: response #> * Feature types: logical, integer, numeric, character, factor, ordered #> * Properties: multiclass, twoclass, weights
# available parameters: learner$param_set$ids()
#> [1] "rhs" "fit" "offset" "cluster" "alpha" #> [6] "bonferroni" "minsize" "minsplit" "minbucket" "maxvar" #> [11] "maxdepth" "mtry" "trim" "breakties" "parm" #> [16] "dfsplit" "prune" "restart" "verbose" "caseweights" #> [21] "ytype" "xtype" "terminal" "inner" "model" #> [26] "numsplit" "catsplit" "vcov" "ordinal" "nrep" #> [31] "applyfun" "cores" "additional" "predict_fun"