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Content Provider | IEEE Xplore Digital Library |
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Author | Zhenyu Guo Ward, M.O. Rundensteiner, E.A. |
Copyright Year | 2009 |
Description | Author affiliation: Computer Science Department, Worcester Polytechnic Institute, USA (Zhenyu Guo; Ward, M.O.; Rundensteiner, E.A.) |
Abstract | 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 linear relationships intuitively, especially when more than 3 variables are involved or multiple trends coexist in the dataset. We present a novel multivariate model parameter space visualization system that helps analysts discover single and multiple linear patterns and extract subsets of data that fit a model well. Using this system, analysts are able to explore and navigate in model parameter space, interactively select and tune patterns, and refine the model for accuracy using computational techniques. We build connections between model space and data space visually, allowing analysts to employ their domain knowledge during exploration to better interpret the patterns they discover and their validity. Case studies with real datasets are used to investigate the effectiveness of the visualizations. |
Starting Page | 75 |
Ending Page | 82 |
File Size | 1252446 |
Page Count | 8 |
File Format | |
ISBN | 9781424452835 |
DOI | 10.1109/VAST.2009.5333431 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2009-10-12 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Data analysis Navigation Extraterrestrial phenomena model space visualization Scattering Knowledge Discovery Predictive models Data mining multivariate linear model construction Computer science visual analysis Data visualization User interfaces Pattern analysis |
Content Type | Text |
Resource Type | Article |
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