Print Maxent Model Results

Prints a summary of Maxent model performance metrics to the console, replicating the style of the dismo package's MaxEnt output. The report includes sample counts, training (and optionally test) evaluation statistics, and a ranked variable-contributions table.

Usage

maxent_print_results(
  species,
  eval_result,
  contributions_df,
  perm_imp_df,
  n_presence,
  n_background,
  test_eval_result = NULL,
  n_test = 0L,
  fit_result = NULL
)

Arguments

species

Character: species name.

eval_result

Named list returned by maxent_evaluate (training predictions vs background).

contributions_df

Data.frame with columns name and contribution (from maxent_percent_contribution).

perm_imp_df

Data.frame with columns name and permutation_importance (from maxent_permutation_importance).

n_presence

Integer: number of training presence records.

n_background

Integer: number of background records.

test_eval_result

Named list returned by maxent_evaluate for test data, or NULL (default).

n_test

Integer: number of test presence records (default 0L).

fit_result

Named list returned by maxent_fit or NULL. Used to report regularized training gain and entropy.

Value

Invisibly returns a named list with all reported metrics.

Examples

# \donttest{
eval_result <- maxent_evaluate(c(0.9, 0.85, 0.95), c(0.1, 0.15, 0.2))
contrib <- data.frame(name = c("bio1", "bio12"),
                      contribution = c(60, 40))
perm_imp <- data.frame(name = c("bio1", "bio12"),
                       permutation_importance = c(55, 45))
maxent_print_results(
  species          = "Sp1",
  eval_result      = eval_result,
  contributions_df = contrib,
  perm_imp_df      = perm_imp,
  n_presence       = 3L,
  n_background     = 100L)
#> class         : MaxEnt
#> species       : Sp1
#> n presence    : 3
#> n background  : 100
#> 
#> Training statistics
#>   AUC             : 1.0000
#> 
#> Variable contributions
#>   Variable              Contribution (%)  Permutation importance (%)
#>   bio1                              60.0                       55.0
#>   bio12                             40.0                       45.0
#> 
# }