cuerank

cue.df

A logical vector of length m containing criterion values for exemplars in cue.df

criterion.v

A string indicating how to rank cues. "v" = HR - FAR, "d" = d-prime.

tree.criterion

A string indicating how to calculate cue splitting thresholds. "m" = median split, "o" = split that maximizes the tree criterion.

numthresh.method

A number between 0 and 1 indicating how much weight to give to increasing hit rates versus avoiding false alarms. 1 means maximizing HR and ignoring FAR, while 0 does the opposite. The default of 0.5 gives equal weight to both.

hr.weight

An integer indicating digit rounding for non-integer numeric cue thresholds. The default is NULL which means no rounding. A value of 0 rounds all possible thresholds to the nearest integer, 1 rounds to the nearest .1 (etc.).

rounding

A logical value indicating whether or not to print ongoing diagnostics

verbose


Calculate the accuracy of all cues in a dataframe


Contains several functions that allow users
to create, visualize, and test Fast and Frugal Trees (FFTs). FFts are very simple decision trees for
classifying cases (i.e.; breast cancer patients) into one of two classes (e.g.;
no cancer vs. true cancer) based on a small number of cues (e.g.; test results). FFTs can be preferable to more complex algorithms (such as
logistic regression) because they are easy to communicate and implement, and are
robust against noisy data.

cuerank: Calculate the accuracy of all cues in a dataframe

Description

Usage

Arguments

Value