MachineShop (version 2.0.0)

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.

Value

MLModel class object.

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.

See Also

earth, fit, resample

Examples

# NOT RUN {
model_fit <- fit(Species ~ ., data = iris, model = EarthModel)
varimp(model_fit, metric = "nsubsets", scale = FALSE)

# }