mlr_learners_regr.cforest.Rd
Calls partykit::cforest from package partykit.
This Learner can be instantiated via the
dictionary mlr_learners or with the associated
sugar function lrn()
:
mlr_learners$get("regr.cforest") lrn("regr.cforest")
Packages: partykit, sandwich, coin
Predict Types: response
Feature Types: integer, numeric, factor, ordered
Properties: oob_error, weights
Hothorn T, Zeileis A (2015). “partykit: A Modular Toolkit for Recursive Partytioning in R.” Journal of Machine Learning Research, 16(118), 3905-3909. http://jmlr.org/papers/v16/hothorn15a.html
Hothorn T, Hornik K, Zeileis A (2006). “Unbiased Recursive Partitioning: A Conditional Inference Framework.” Journal of Computational and Graphical Statistics, 15(3), 651–674. doi: 10.1198/106186006x133933
sumny
mlr3::Learner
-> mlr3::LearnerRegr
-> LearnerRegrCForest
new()
Creates a new instance of this R6 class.
LearnerRegrCForest$new()
oob_error()
The out-of-bag error, calculated using the OOB predictions from
partykit
.
LearnerRegrCForest$oob_error()
clone()
The objects of this class are cloneable with this method.
LearnerRegrCForest$clone(deep = FALSE)
deep
Whether to make a deep clone.
# stop example failing with warning if package not installed learner = suppressWarnings(mlr3::lrn("regr.cforest")) print(learner)#> <LearnerRegrCForest:regr.cforest> #> * Model: - #> * Parameters: teststat=quadratic, testtype=Univariate, mincriterion=0, #> saveinfo=FALSE #> * Packages: partykit, sandwich, coin #> * Predict Type: response #> * Feature types: integer, numeric, factor, ordered #> * Properties: oob_error, weights# available parameters: learner$param_set$ids()#> [1] "ntree" "replace" "fraction" "mtry" #> [5] "applyfun" "cores" "trace" "offset" #> [9] "cluster" "scores" "teststat" "splitstat" #> [13] "splittest" "testtype" "nmax" "pargs" #> [17] "alpha" "mincriterion" "logmincriterion" "minsplit" #> [21] "minbucket" "minprob" "stump" "lookahead" #> [25] "MIA" "maxvar" "nresample" "tol" #> [29] "maxsurrogate" "numsurrogate" "maxdepth" "multiway" #> [33] "splittry" "intersplit" "majority" "caseweights" #> [37] "saveinfo" "update" "splitflavour" "OOB" #> [41] "simplify" "scale" "nperm" "risk" #> [45] "conditional" "threshold"