dc.contributor.author |
Van der Walt, Christiaan M
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|
dc.contributor.author |
Barnard, E
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|
dc.date.accessioned |
2012-02-14T15:15:52Z |
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dc.date.available |
2012-02-14T15:15:52Z |
|
dc.date.issued |
2009-11 |
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dc.identifier.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 |
en_US |
dc.identifier.isbn |
978-0-7992-2356-9 |
|
dc.identifier.uri |
http://www.dip.ee.uct.ac.za/prasa/PRASA2010/proceedings/2009/prasa09-23.pdf
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|
dc.identifier.uri |
http://www.dip.ee.uct.ac.za/prasa/PRASA2010/proceedings/2009/
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|
dc.identifier.uri |
http://hdl.handle.net/10204/5568
|
|
dc.description |
20th Annual Symposium of the Pattern Recognition Association of South Africa (PRASA), Stellenbosch, South Africa, 30 November-01 December 2009 |
en_US |
dc.description.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. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
PRASA |
en_US |
dc.subject |
Density estimation |
en_US |
dc.subject |
Hyper-ellipsoids |
en_US |
dc.subject |
Gaussian mixture model (GMM) |
en_US |
dc.subject |
Local structure |
en_US |
dc.title |
Density estimation from local structure |
en_US |
dc.type |
Conference Presentation |
en_US |
dc.identifier.apacitation |
Van der Walt, C. M., & Barnard, E. (2009). Density estimation from local structure. PRASA. http://hdl.handle.net/10204/5568 |
en_ZA |
dc.identifier.chicagocitation |
Van der Walt, Christiaan M, and E Barnard. "Density estimation from local structure." (2009): http://hdl.handle.net/10204/5568 |
en_ZA |
dc.identifier.vancouvercitation |
Van der Walt CM, Barnard E, Density estimation from local structure; PRASA; 2009. http://hdl.handle.net/10204/5568 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Van der Walt, Christiaan M
AU - Barnard, E
AB - 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.
DA - 2009-11
DB - ResearchSpace
DP - CSIR
KW - Density estimation
KW - Hyper-ellipsoids
KW - Gaussian mixture model (GMM)
KW - Local structure
LK - https://researchspace.csir.co.za
PY - 2009
SM - 978-0-7992-2356-9
T1 - Density estimation from local structure
TI - Density estimation from local structure
UR - http://hdl.handle.net/10204/5568
ER -
|
en_ZA |