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General Recognition Theory is a Psychological model of how people might form linear decision boundaries among stimuli.
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README.rst

General Recognition Theory

General Recognition Theory is a multi-dimensional version of signal detection theory (Thurstone, 1927; Green & Swets, 1966). It was developed by psychologists (Ashby & Townsend, 1986; Ashby & Gott, 1988) to study the human categorization process.

General Recognition Theory (hereafter GRT) is a model developed by Ashby and collaborators (Ashby & Townsend, 1986; Ashby & Gott, 1988) as a Psychologically realistic thoery of how humans might derive boundaries through stimulus space for the purpose of categorization. It is essentially a multi-dimensional version of signal detection theory [wiki].

It is commonly used as an analysis method to infer the decision boundary participants were using after they have labeled stimuli in a categorization experiment.

What is this doing here?

I have forked a lovely Matlab toollbox put together by Leola Alfonso-Reese. She has it hosted on her website. I was working on moving it over to Python for my own research, and realized I should make my efforts public. All files are marked internally with copyright information, and global copyright information about the Matlab toolkit can be found in matlab/GRT_README.m. You should assume all Matlab files are copyrighted by her and subject to the terms of her readme file. I have made minimal changes to the Matlab files, focusing instead on porting the code over to Python. Work by me (all the Python files) is copyrighted by me, but I assent to copying for personal or academic reasons. I do not assent to any copying or publication for any commercial reason without my express written consent. I also make no claim that the work provide here is useful for any particular purpose, and am not responsible for any ill that may befall you as a result of using it.

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