mlr_learners_classif.earth.Rd
Calls earth::earth from package earth.
Methods for variance estimations are not yet implemented.
This Learner can be instantiated via the
dictionary mlr_learners or with the associated
sugar function lrn()
:
mlr_learners$get("classif.earth") lrn("classif.earth")
Packages: earth
Predict Types: response, prob
Feature Types: numeric, factor, integer
Properties: twoclass, weights
Stephen Milborrow (2014) Earth: multivariate adaptive regression spline models R package version 3 https://cran.r-project.org/web/packages/earth/earth.pdf
Jerome H. Friedman (1991) Multivariate Adaptive Regression Splines The Annals of Statistics https://projecteuclid.org/download/pdf_1/euclid.aos/1176347963
pkopper
mlr3::Learner
-> mlr3::LearnerClassif
-> LearnerClassifEarth
new()
Creates a new instance of this R6 class.
LearnerClassifEarth$new()
clone()
The objects of this class are cloneable with this method.
LearnerClassifEarth$clone(deep = FALSE)
deep
Whether to make a deep clone.
# stop example failing with warning if package not installed learner = suppressWarnings(mlr3::lrn("classif.earth")) print(learner)#> <LearnerClassifEarth:classif.earth> #> * Model: - #> * Parameters: list() #> * Packages: earth #> * Predict Type: response #> * Feature types: numeric, factor, integer #> * Properties: twoclass, weights# available parameters: learner$param_set$ids()#> [1] "wp" "offset" "keepxy" "trace" #> [5] "degree" "penalty" "nk" "thresh" #> [9] "minspan" "endspan" "newvar.penalty" "fast.k" #> [13] "fast.beta" "linpreds" "allowed" "pmethod" #> [17] "nprune" "nfold" "ncross" "stratify" #> [21] "varmod.method" "varmod.exponent" "varmod.conv" "varmod.clamp" #> [25] "varmod.minspan" "Scale.y" "Adjust.endspan" "Auto.linpreds" #> [29] "Force.weights" "Use.beta.cache" "Force.xtx.prune" "Get.leverages" #> [33] "Exhaustive.tol"