MachineShop: EarthModel – R documentation

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EarthModel

Multivariate Adaptive Regression Splines Model

Description

Build a regression model using the techniques in Friedman's papers "Multivariate Adaptive Regression Splines" and "Fast MARS".

Usage

EarthModel(
  pmethod = c("backward", "none", "exhaustive", "forward", "seqrep", "cv"),
  trace = 0,
  degree = 1,
  nprune = NULL,
  nfold = 0,
  ncross = 1,
  stratify = TRUE
)

Arguments

`pmethod`	pruning method.
`trace`	level of execution information to display.
`degree`	maximum degree of interaction.
`nprune`	maximum number of terms (including intercept) in the pruned model.
`nfold`	number of cross-validation folds.
`ncross`	number of cross-validations if `nfold > 1`.
`stratify`	logical indicating whether to stratify cross-validation samples by the response levels.

Details

Response Types:: factor, numeric
Automatic Tuning of Grid Parameters:: nprune, degree*

* included only in randomly sampled grid points

Default values for the NULL arguments and further model details can be found in the source link below.

In calls to varimp for EarthModel, argument metric may be specified as "gcv" (default) for the generalized cross-validation decrease over all subsets that include each predictor, as "rss" for the residual sums of squares decrease, or as "nsubsets" for the number of model subsets that include each predictor. Variable importance is automatically scaled to range from 0 to 100. To obtain unscaled importance values, set scale = FALSE. See example below.

Value

MLModel class object.

Examples

## Requires prior installation of suggested package earth to run

model_fit <- fit(Species ~ ., data = iris, model = EarthModel)
varimp(model_fit, metric = "nsubsets", scale = FALSE)

MachineShop

Machine Learning Models and Tools

v2.8.0

GPL-3

Authors

Brian J Smith [aut, cre]

Initial release

2021-04-16