fftrees_cuerank: Calculate thresholds that optimize some statistic (goal) for...

In ndphillips/FFTrees: Generate, Visualise, and Evaluate Fast-and-Frugal Decision Trees

Calculate thresholds that optimize some statistic (goal) for cues in data

Description

fftrees_cuerank takes an FFTrees object x and optimizes its goal.threshold (from x$params) for all cues in newdata (of type data).

Usage

fftrees_cuerank(x = NULL, newdata = NULL, data = "train", rounding = NULL)

Arguments

x	An FFTrees object.
newdata	A dataset with cues to be ranked (as data frame).
data	The type of data with cues to be ranked (as character: 'train', 'test', or 'dynamic'). Default: data = 'train'.
rounding	integer. An integer value indicating the decimal digit to which non-integer numeric cue thresholds are to be rounded. Default: rounding = NULL (i.e., no rounding).

Details

fftrees_cuerank creates a data frame cuerank_df that is added to x$cues$stats.

Note that the cue directions and thresholds computed by FFTrees always predict positive criterion values (i.e., TRUE or signal, rather than FALSE or noise). Using these thresholds for negative exits (i.e., for predicting instances of FALSE or noise) usually requires a reversal (e.g., negating cue direction).

fftrees_cuerank is called (twice) by the fftrees_grow_fan algorithm to grow fast-and-frugal trees (FFTs).

Value

A modified FFTrees object (with cue rank information for the current data type in x$cues$stats).

ndphillips/FFTrees documentation built on April 25, 2024, 1:07 a.m.