Measures how much each environmental variable contributes to model prediction quality by permuting each variable and measuring AUC drop.
Usage
compute_permutation_importance(
fs_ptr,
grid_ptrs,
feature_names,
presence_rows,
presence_cols,
absence_rows,
absence_cols,
seed = 42L
)Arguments
- fs_ptr
External pointer to a FeaturedSpace object.
- grid_ptrs
List of external pointers to Grid<float> objects.
- feature_names
Character vector of environment variable names.
- presence_rows
Integer vector of presence site row indices.
- presence_cols
Integer vector of presence site column indices.
- absence_rows
Integer vector of absence site row indices.
- absence_cols
Integer vector of absence site column indices.
- seed
Random seed for reproducibility.