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36 - Model Validation, Comparison, and Selection

from Part V - General Discussion

Published online by Cambridge University Press:  21 April 2023

By
Leslie M. Blaha  and
Kevin A. Gluck
Edited by
Ron Sun
Ron Sun
Affiliation:
Rensselaer Polytechnic Institute, New York
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Summary

Progress in the computational cognitive sciences depends critically on model evaluation. This chapter provides an accessible description of key considerations and methods important in model evaluation, with special emphasis on evaluation in the forms of validation, comparison, and selection. Major sub-topics include qualitative and quantitative validation, parameter estimation, cross-validation, goodness of fit, and model mimicry. The chapter includes definitions of an assortment of key concepts, relevant equations, and descriptions of best practices and important considerations in the use of these model evaluation methods. The chapter concludes with important high-level considerations regarding emerging directions and opportunities for continuing improvement in model evaluation.

Keywords

quantitative evaluationqualitative evaluationmodel validationmodel comparisonmodel selectiongoodness of fitcognitive modeling
Type
Chapter
Information
The Cambridge Handbook of Computational Cognitive Sciences , pp. 1165 - 1200
Publisher: Cambridge University Press
Print publication year: 2023

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