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Fits an SDM workflow to data using resampling and prepares it for stacking.

Source: R/h3sdm_fit_model.R
h3sdm_fit_model.Rd

Fits a Species Distribution Model (SDM) workflow to resampling data (cross-validation). This function is the main training step and optionally configures the results to be used with the 'stacks' package.

Usage

h3sdm_fit_model(
  workflow,
  data_split,
  presence_data = NULL,
  truth_col = "presence",
  pred_col = ".pred_1",
  for_stacking = FALSE,
  ...
)

Arguments

workflow

A 'workflow' object from tidymodels (e.g., GAM or Random Forest).

data_split

An 'rsplit' or 'rset' object (e.g., result of vfold_cv or spatial_block_cv).

presence_data

(Optional) Original presence data (used for extended metrics).

truth_col

Column name of the response variable (defaults to "presence").

pred_col

Column name for the prediction of the class of interest (defaults to ".pred_1").

for_stacking

Logical. If TRUE, uses control_stack_resamples() to save all workflow information required for the 'stacks' package. If FALSE, uses the standard control with save_pred = TRUE.

...

Arguments passed on to other functions (e.g., to tune::fit_resamples if needed).

Value

A list with three elements:

  • cv_model: The result of fit_resamples().

  • final_model: The model fitted to the entire training set (first split).

  • metrics: Extended evaluation metrics (if presence_data is provided).