EarthModel {MachineShop} | 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 = NULL, 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
*
* 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.
MLModel
class object.
## Requires prior installation of suggested package earth to run model_fit <- fit(Species ~ ., data = iris, model = EarthModel) varimp(model_fit, metric = "nsubsets", scale = FALSE)