optim_thresh {tidysdm}

Find threshold that optimises a given metric

Description

This function returns the threshold to turn probabilities into binary classes whilst optimising a given metric. Currently available for tss_max, kap_max and sensitivity (for which a target sensitivity is required).

Usage

optim_thresh(truth, estimate, metric, event_level = "first")

Arguments

truth

The column identifier for the true class results (that is a factor). This should be an unquoted column name although this argument is passed by expression and supports quasiquotation (you can unquote column names). For _vec() functions, a factor vector.

estimate

the predicted probability for the event

metric

character of metric to be optimised. Currently only "tss_max", "kap_max", and "sensitivity" with a given target (e.g. c("sensitivity",0.8))

event_level

A single string. Either "first" or "second" to specify which level of truth to consider as the "event". This argument is only applicable when estimator = "binary". The default uses an internal helper that generally defaults to "first"

Value

the probability threshold for the event

Examples

optim_thresh(two_class_example$truth, two_class_example$Class1, metric = c("tss_max"))
optim_thresh(two_class_example$truth, two_class_example$Class1, metric = c("sens", 0.9))