sdm_spec_rand_forest: Model specification for a Random Forest for SDM

In tidysdm: Species Distribution Models with Tidymodels

Model specification for a Random Forest for SDM

Description

This function returns a parsnip::model_spec for a Random Forest to be used as a classifier of presences and absences in Species Distribution Models. It uses the library ranger to fit boosted trees; to use another library, simply build the parsnip::model_spec directly.

Usage

sdm_spec_rand_forest(..., tune = c("sdm", "all", "custom", "none"))

sdm_spec_rf(..., tune = c("sdm", "all", "custom", "none"))

Arguments

...	parameters to be passed to parsnip::rand_forest() to customise the model. See the help of that function for details.
tune	character defining the tuning strategy. Valid strategies are: "sdm" chooses hyperparameters that are most important to tune for an sdm (for rf, 'mtry') "all" tunes all hyperparameters (for rf, 'mtry', 'trees' and 'min') "custom" passes the options from '...' "none" does not tune any hyperparameter

Details

sdm_spec_rf() is simply a short form for sm_spec_rand_forest().

Value

a parsnip::model_spec of the model.

See Also

Other "sdm model specifications": sdm_spec_boost_tree(), sdm_spec_gam(), sdm_spec_glm(), sdm_spec_maxent()

Examples

test_rf_spec <- sdm_spec_rf(tune = "sdm")
test_rf_spec
# combining tuning with specific values for other hyperparameters
sdm_spec_rf(tune = "sdm", trees = 100)

tidysdm documentation built on April 3, 2025, 9:56 p.m.