threshold | R Documentation |
Find a threshold (cut-off) to transform model predictions (probabilities, distances, or similar values) to a binary score (presence or absence).
## S4 method for signature 'paModelEvaluation'
threshold(x)
x |
paModelEvaluation object (see |
data.frame with the following columns:
kappa: the threshold at which kappa is highest ("max kappa")
spec_sens: the threshold at which the sum of the sensitivity (true positive rate) and specificity (true negative rate) is highest
no_omission: the highest threshold at which there is no omission
prevalence: modeled prevalence is closest to observed prevalence
equal_sens_spec: equal sensitivity and specificity
Robert J. Hijmans and Diego Nieto-Lugilde
pa_evaluate
## See ?maxent for an example with real data.
# this is a contrived example:
# p has the predicted values for 50 known cases (locations)
# with presence of the phenomenon (species)
p <- rnorm(50, mean=0.7, sd=0.3)
# b has the predicted values for 50 background locations (or absence)
a <- rnorm(50, mean=0.4, sd=0.4)
e <- pa_evaluate(p=p, a=a)
threshold(e)
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