enmpa (version 0.2.1)

optimize_metrics: Find threshold values to produce three optimal metrics

Description

The metrics true skill statistic (TSS), sensitivity, specificity are explored by comparing actual vs predicted values to find threshold values that produce sensitivity = specificity, maximum TSS, and a sensitivity value of 0.9.

Usage

optimize_metrics(actual, predicted, n_threshold = 100)

Value

A list containing a data.frame with the resulting metrics for all threshold values tested, and a second data.frame with the results for the threshold values that produce sensitivity = specificity (ESS), maximum TSS (maxTSS), and a sensitivity value of 0.9 (SEN90).

Arguments

actual

(numeric) vector of actual values (0, 1) to be compared to predicted values after applying a threshold.

predicted

(numeric) vector of predicted probability values to be thresholded and compared to actual.

n_threshold

(numeric) number of threshold values to be used. Default = 100.

Examples

# example data
act <- c(rep(1, 20), rep(0, 80))
pred <- c(runif(20, min = 0.4, max = 0.7), runif(80, min = 0, max = 0.5))

# run example
om <- optimize_metrics(actual = act, predicted = pred)
om$optimized