DocumentCode
2617851
Title
Selecting the optimal number of components for a Gaussian mixture model
Author
McKenzie, Patricia ; Alder, Michael
Author_Institution
Centre for Intelligent Inf. Process. Syst., Western Australia Univ., Nedlands, WA, Australia
fYear
1994
fDate
27 Jun-1 Jul 1994
Firstpage
393
Abstract
We compare two approaches to determining the optimal number of component Gaussians to include in a Gaussian mixture model, the Akaike information criterion and the Rissanen (1989) minimum description length method
Keywords
Gaussian distribution; Gaussian processes; information theory; Akaike information criterion; Gaussian distribution; Gaussian mixture model; minimum description length method; mixture components; Algebra; Australia; Cost function; Gaussian distribution; Gaussian processes; Information processing; Intelligent systems; Probability density function; Probability distribution; Random variables;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 1994. Proceedings., 1994 IEEE International Symposium on
Conference_Location
Trondheim
Print_ISBN
0-7803-2015-8
Type
conf
DOI
10.1109/ISIT.1994.394626
Filename
394626
Link To Document