IDENTIFYING THE NUMBER OF COMPONENTS IN GAUSSIAN MIXTURE MODELS USING NUMERICAL ALGEBRAIC GEOMETRY

Using Gaussian mixture models for clustering is a statistically mature method for clustering in data science with numerous successful applications in science and engineering. The parameters for a Gaussian mixture model are typically estimated from training data using the iterative expectation-maximi...

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Bibliographic Details

Published in:	Journal of algebra and its applications Vol. 19; no. 11
Main Authors:	Shirinkam, Sara, Alaeddini, Adel, Gross, Elizabeth
Format:	Journal Article
Language:	English
Published:	Singapore 01.11.2020
Subjects:	numerical algebraic geometry smoothing spline model-based clustering Mixture models
ISSN:	1793-6829, 1793-6829
Online Access:	Get more information
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