An interactive scatter plot metrics visualization for decision trend analysis

Huang, TH; Huang, ML; Zhang, K

An interactive scatter plot metrics visualization for decision trend analysis

Huang, TH Huang, ML

Zhang, K

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012, 2012, 2 pp. 258 - 264
Issue Date:: 2012-12-01

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Field	Value	Language
dc.contributor.author	Huang, TH	en_US
dc.contributor.author	Huang, ML https://orcid.org/0000-0002-6896-6480	en_US
dc.contributor.author	Zhang, K	en_US
dc.date.issued	2012-12-01	en_US
dc.identifier.citation	Proceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012, 2012, 2 pp. 258 - 264	en_US
dc.identifier.isbn	9780769549132	en_US
dc.identifier.uri	http://hdl.handle.net/10453/22921
dc.description.abstract	This paper presents a new interactive scatter plot visualization for multi-dimensional data analysis. We apply RST to reduce the visual complexity through dimensionality reduction. We use an innovative point-to-region mouse click concept to enable direct interactions with scatter points that are theoretically impossible. To show the decision trend we use a virtual Z dimension to display a set of linear flows showing approximation of the decision trend. We have conducted a case study to demonstrate the effectiveness and usefulness of our new technique for identifying the impact sources of wine quality through the visual analytics of a wine dataset consisting of 12 attributes with 4898 samples. © 2012 IEEE.	en_US
dc.relation.ispartof	Proceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012	en_US
dc.relation.isbasedon	10.1109/ICMLA.2012.164	en_US
dc.title	An interactive scatter plot metrics visualization for decision trend analysis	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Boca Raton, FL, USA	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	2	en_US

Abstract:

This paper presents a new interactive scatter plot visualization for multi-dimensional data analysis. We apply RST to reduce the visual complexity through dimensionality reduction. We use an innovative point-to-region mouse click concept to enable direct interactions with scatter points that are theoretically impossible. To show the decision trend we use a virtual Z dimension to display a set of linear flows showing approximation of the decision trend. We have conducted a case study to demonstrate the effectiveness and usefulness of our new technique for identifying the impact sources of wine quality through the visual analytics of a wine dataset consisting of 12 attributes with 4898 samples. © 2012 IEEE.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/22921