Computes all evaluation metrics at once: AUC, correlation, log-loss,
squared error, misclassification, max Kappa, and prevalence.
Usage
maxent_evaluate(presence, absence)
Arguments
- presence
Numeric vector of prediction scores at presence sites.
- absence
Numeric vector of prediction scores at absence sites.
Value
A named list with:
- auc
AUC value
- max_kappa
Best Cohen's Kappa
- max_kappa_thresh
Threshold at best Kappa
- correlation
Pearson correlation with labels
- square_error
Mean squared error
- logloss
Cross-entropy log-loss
- misclassification
Misclassification rate
- prevalence
Fraction of presence sites
Examples
res <- maxent_evaluate(c(0.9, 0.85, 0.95), c(0.1, 0.15, 0.2))
res$auc # 1.0
#> [1] 1
res$correlation # > 0
#> [1] 0.9941262
