Model space visualization for multivariate linear trend discovery

Discovering and extracting linear trends and correlations in datasets is very important for analysts to understand multivariate phenomena. However, current widely used multivariate visualization techniques, such as parallel coordinates and scatterplot matrices, fail to reveal and illustrate such lin...

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Bibliographic Details

Published in:	2009 IEEE Symposium on Visual Analytics Science and Technology pp. 75 - 82
Main Authors:	Zhenyu Guo, Ward, M.O., Rundensteiner, E.A.
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.10.2009
Subjects:	Computer science Data analysis Data mining Data visualization Extraterrestrial phenomena Knowledge Discovery model space visualization multivariate linear model construction Navigation Pattern analysis Predictive models Scattering User interfaces visual analysis
ISBN:	9781424452835, 142445283X
Online Access:	Get full text
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