Classification MARS (Multivariate Adaptive Regression Splines) Learner

Calls earth::earth from package earth.

Details

Methods for variance estimations are not yet implemented.

Dictionary

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")

Meta Information

• Task type: “classif”

• Predict Types: “response”, “prob”

• Feature Types: “numeric”, “factor”, “integer”

• Required Packages: mlr3extralearners, earth

Parameters

Id	Type	Default	Levels	Range
wp	list	NULL		\((-\infty, \infty)\)
offset	list	NULL		\((-\infty, \infty)\)
keepxy	logical	FALSE	TRUE, FALSE	\((-\infty, \infty)\)
trace	character	0	0, .3, .5, 1, 2, 3, 4, 5	\((-\infty, \infty)\)
degree	integer	1		\([1, \infty)\)
penalty	numeric	2		\([-1, \infty)\)
nk	list	NULL		\((-\infty, \infty)\)
thresh	numeric	0.001		\((-\infty, \infty)\)
minspan	numeric	0		\([0, \infty)\)
endspan	numeric	0		\([0, \infty)\)
newvar.penalty	numeric	0		\([0, \infty)\)
fast.k	integer	20		\([0, \infty)\)
fast.beta	integer	1		\([0, 1]\)
linpreds	list	FALSE		\((-\infty, \infty)\)
allowed	list	-		\((-\infty, \infty)\)
pmethod	character	backward	backward, none, exhaustive, forward, seqrep, cv	\((-\infty, \infty)\)
nprune	integer	-		\([0, \infty)\)
nfold	integer	0		\([0, \infty)\)
ncross	integer	1		\([0, \infty)\)
stratify	logical	TRUE	TRUE, FALSE	\((-\infty, \infty)\)
varmod.method	character	none	none, const, lm, rlm, earth, gam, power, power0, x.lm, x.rlm, ...	\((-\infty, \infty)\)
varmod.exponent	numeric	1		\((-\infty, \infty)\)
varmod.conv	numeric	1		\([0, 1]\)
varmod.clamp	numeric	0.1		\((-\infty, \infty)\)
varmod.minspan	numeric	-3		\((-\infty, \infty)\)
Scale.y	logical	FALSE	TRUE, FALSE	\((-\infty, \infty)\)
Adjust.endspan	numeric	2		\((-\infty, \infty)\)
Auto.linpreds	logical	TRUE	TRUE, FALSE	\((-\infty, \infty)\)
Force.weights	logical	FALSE	TRUE, FALSE	\((-\infty, \infty)\)
Use.beta.cache	logical	TRUE	TRUE, FALSE	\((-\infty, \infty)\)
Force.xtx.prune	logical	FALSE	TRUE, FALSE	\((-\infty, \infty)\)
Get.leverages	logical	TRUE	TRUE, FALSE	\((-\infty, \infty)\)
Exhaustive.tol	numeric	1e-10		\((-\infty, \infty)\)

References

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

See also

• Dictionary of Learners: mlr3::mlr_learners.

• as.data.table(mlr_learners) for a table of available Learners in the running session (depending on the loaded packages).

• Chapter in the mlr3book: https://mlr3book.mlr-org.com/basics.html#learners

• mlr3learners for a selection of recommended learners.

• mlr3cluster for unsupervised clustering learners.

• mlr3pipelines to combine learners with pre- and postprocessing steps.

• mlr3tuning for tuning of hyperparameters, mlr3tuningspaces for established default tuning spaces.

Author

pkopper

Super classes

mlr3::Learner -> mlr3::LearnerClassif -> LearnerClassifEarth

Methods

Public methods

• LearnerClassifEarth$new()

• LearnerClassifEarth$clone()

Inherited methods

• mlr3::Learner$base_learner()

• mlr3::Learner$format()

• mlr3::Learner$help()

• mlr3::Learner$predict()

• mlr3::Learner$predict_newdata()

• mlr3::Learner$print()

• mlr3::Learner$reset()

• mlr3::Learner$train()

---

Method new()

Creates a new instance of this R6 class.

Usage

LearnerClassifEarth$new()

---

Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerClassifEarth$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

if (requireNamespace("earth", quietly = TRUE)) {
  learner = mlr3::lrn("classif.earth")
  print(learner)

  # available parameters:
  learner$param_set$ids()
}
#> <LearnerClassifEarth:classif.earth>
#> * Model: -
#> * Parameters: list()
#> * Packages: mlr3, mlr3extralearners, earth
#> * Predict Type: response
#> * Feature types: numeric, factor, integer
#> * Properties: twoclass, weights
#>  [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"