Skip to contents

Fit a linear model with a response-surface component. Calls rsm::rsm() from rsm.

Custom mlr3 parameters

  • modelfun: This parameter controls how the formula for rsm::rsm() is created. Possible values are:

    • "FO" - first order

    • "TWI" - wo-way interactions, this is with 1st oder terms

    • "SO" - full second order

Dictionary

This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn():

mlr_learners$get("regr.rsm")
lrn("regr.rsm")

Meta Information

  • Task type: “regr”

  • Predict Types: “response”

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

  • Required Packages: mlr3, rsm

Parameters

IdTypeDefaultLevels
modelfuncharacterFOFO, TWI, SO

References

Lenth, V R (2010). “Response-surface methods in R, using rsm.” Journal of Statistical Software, 32, 1--17.

See also

Author

sebffischer

Super classes

mlr3::Learner -> mlr3::LearnerRegr -> LearnerRegrRSM

Methods

Inherited methods


Method new()

Creates a new instance of this R6 class.

Usage


Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerRegrRSM$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

learner = mlr3::lrn("regr.rsm")
print(learner)
#> <LearnerRegrRSM:regr.rsm>: Response Surface Model
#> * Model: -
#> * Parameters: modelfun=FO
#> * Packages: mlr3, rsm
#> * Predict Types:  [response]
#> * Feature Types: integer, numeric, factor, ordered
#> * Properties: -

# available parameters:
learner$param_set$ids()
#> [1] "modelfun"