Premium
Choice‐based experiments in multiple dimensions
Author(s) -
Lichtenauer Matthias Scheller,
Zolliker Peter,
Sprow Iris
Publication year - 2013
Publication title -
color research and application
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.393
H-Index - 62
eISSN - 1520-6378
pISSN - 0361-2317
DOI - 10.1002/col.21723
Subject(s) - perception , computer science , artificial intelligence , machine learning , stimulus (psychology) , generalized linear model , cognitive psychology , psychology , neuroscience
Color technology needs specifications to which extent physical differences of stimuli correspond to differences in perception. Generalized linear models (GLMs) have proved successful to provide such specifications from choice‐based experiments. However, the use of GLMs imposes practical restrictions on the experiment and stimulus parameters. We propose an alternative analytic approach based on machine learning and demonstrate its use in designing and analyzing choice‐based experiments with multiple stimulus dimensions. © 2012 Wiley Periodicals, Inc. Col Res Appl, 38, 334–343, 2013