threshold_numeric_grid

numeric. A vector of thresholds to consider

thresholds

cue.v

criterion.v

character. Possible directions to consider

directions

sens.w

numeric. Cost to add to each value (e.g.; cost of the cue)

cost.each

list. A list of length 4 with names 'hi', 'fa', 'mi', and 'cr' specifying the costs of a hit, false alarm, miss, and correct rejection rspectively. E.g.; <code>cost.outcomes = listc("hi" = 0, "fa" = 10, "mi" = 20, "cr" = 0)</code> means that a false alarm and miss cost 10 and 20 respectively while correct decisions have no cost.

cost.outcomes

character. A string indicating the statistic to maximize when calculting cue thresholds: "acc" = overall accuracy, "wacc" = weighted accuracy, "bacc" = balanced accuracy

goal.threshold

Performs a grid search over thresholds and returns accuracy statistics for a given numeric cue

Create, visualize, and test fast-and-frugal decision trees (FFTs). FFTs are very simple decision trees for
binary classification problems. FFTs can be preferable to more complex algorithms because they are easy to communicate, require very little information, and are
robust against overfitting.

threshold_numeric_grid: Performs a grid search over thresholds and returns accuracy statistics for a given numeric cue

Description

Usage

Arguments