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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/5568

Title: Density estimation from local structure
Authors: Van Der Walt, C
Barnard, E
Keywords: Density estimation
Hyper-ellipsoids
Gaussian mixture model (GMM)
Local structure
Issue Date: Nov-2009
Publisher: PRASA
Citation: Van der Walt, C and Barnard, E. Density estimation from local structure. 20th Annual Symposium of the Pattern Recognition Association of South Africa (PRASA), Stellenbosch, South Africa, 30 November-01 December 2009, pp 131-136
Abstract: The authors propose a hyper-ellipsoid clustering algorithm that grows clusters from local structures in a dataset and estimates the underlying geometrical structure of data with a set of hyper-ellipsoids. The clusters are used to estimate a Gaussian Mixture Model (GMM) density function of the data and the log-likelihood scores are compared to the scores of a GMM trained with the expectation maximization (EM) algorithm on 5 real-world classification datasets (from the UCI collection). They show that their approach gives better generalization performance on unseen test sets for 4 of the 5 datasets considered.
Description: 20th Annual Symposium of the Pattern Recognition Association of South Africa (PRASA), Stellenbosch, South Africa, 30 November-01 December 2009
URI: http://www.dip.ee.uct.ac.za/prasa/PRASA2010/proceedings/2009/prasa09-23.pdf
http://www.dip.ee.uct.ac.za/prasa/PRASA2010/proceedings/2009/
http://hdl.handle.net/10204/5568
ISBN: 978-0-7992-2356-9
Appears in Collections:Advanced mathematical modelling and simulation
Digital intelligence
Mobile intelligent autonomous systems
General science, engineering & technology

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