View source: R/ML_EarthModel.R
EarthModel | R Documentation |
Build a regression model using the techniques in Friedman's papers "Multivariate Adaptive Regression Splines" and "Fast MARS".
EarthModel( pmethod = c("backward", "none", "exhaustive", "forward", "seqrep", "cv"), trace = 0, degree = 1, nprune = integer(), nfold = 0, ncross = 1, stratify = TRUE )
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 |
stratify |
logical indicating whether to stratify cross-validation samples by the response levels. |
factor
, numeric
nprune
, degree
*
* excluded from grids by default
Default values and further model details can be found in the source link below.
In calls to varimp
for EarthModel
, argument
type
may be specified as "nsubsets"
(default) for the number of
model subsets that include each predictor, as "gcv"
for the
generalized cross-validation decrease over all subsets that include each
predictor, or as "rss"
for the residual sums of squares decrease.
Variable importance is automatically scaled to range from 0 to 100. To
obtain unscaled importance values, set scale = FALSE
. See example
below.
MLModel
class object.
earth
, fit
,
resample
## Requires prior installation of suggested package earth to run model_fit <- fit(Species ~ ., data = iris, model = EarthModel) varimp(model_fit, method = "model", type = "gcv", scale = FALSE)
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