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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Veröffentlicht in:	2009 IEEE Symposium on Visual Analytics Science and Technology S. 75 - 82
Hauptverfasser:	Zhenyu Guo, Ward, M.O., Rundensteiner, E.A.
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.10.2009
Schlagworte:	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-Zugang:	Volltext
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