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")

Traits

• Packages: earth

• Predict Types: response, prob

• Feature Types: numeric, factor, integer

• Properties: twoclass, weights

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

Author

pkopper

Super classes

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

Methods

Public methods

• LearnerClassifEarth$new()

• LearnerClassifEarth$clone()

Inherited methods

• mlr3::Learner$format()

• mlr3::Learner$help()

• mlr3::Learner$predict()

• mlr3::Learner$predict_newdata()

• mlr3::Learner$print()

• mlr3::Learner$reset()

• mlr3::Learner$train()

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Method new()

Creates a new instance of this R6 class.

Usage

LearnerClassifEarth$new()

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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

# 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"