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Journal article
Learning Factor Patterns in Exploratory Factor Analysis Using the Genetic Algorithm and Information Complexity as the Fitness Function
Journal of pattern recognition research, Vol.6(2), pp.307-326
01/01/2011
Web of Science ID: WOS:000218354000014
Abstract
This paper presents a novel data-adaptive expert approach to determining the best factor pattern structure in exploratory factor analysis (EFA) models using a clever genetic algorithm (GA) hybridized with information theoretic complexity (ICOMP) criterion as the fitness function. These factor pattern structures from EFA model could then be utilized for various inductive inferences for example to study substantive hypotheses of researchers in the light of the data or could be used as data-adaptive prior information in a Bayesian Factor Analysis (BFA) model among other uses. Numerical applications are shown on a large scale Monte Carlo study and on a real benchmark data set to demonstrate the versatility of ICOMP, Akaike's Information Criterion (AIC) as the fitness functions in GA, in two types of modeling problems: (i) Choosing the number of factors in EFA, and (ii) determining the best factor pattern structure in EFA models in one expert system.
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Details
- Title
- Learning Factor Patterns in Exploratory Factor Analysis Using the Genetic Algorithm and Information Complexity as the Fitness Function
- Publication Details
- Journal of pattern recognition research, Vol.6(2), pp.307-326
- Resource Type
- Journal article
- Publisher
- Journal Pattern Recognition Research
- Number of pages
- 20
- Copyright
- c 2011 JPRR. All rights reserved. Permissions to make digital or hard copies of all or part of this work for personal or classroom use may be granted by JPRR provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or to republish, requires a fee and/or special permission from JPRR.
- Identifiers
- WOS:000218354000014; 99380186966306600
- Academic Unit
- School of Education
- Language
- English