Automated Box-Cox Transformations for Improved Visual Encoding

The concept of preconditioning data (utilizing a power transformation as an initial step) for analysis and visualization is well established within the statistical community and is employed as part of statistical modeling and analysis. Such transformations condition the data to various inherent assu...

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Bibliographic Details
Published in:IEEE transactions on visualization and computer graphics 2013-01, Vol.19 (1), p.130-140
Main Authors: Maciejewski, R., Pattath, A., Sungahn Ko, Hafen, R., Cleveland, W. S., Ebert, D. S.
Format: Article
Language:English
Subjects:
automated box-cox transformations
axis transformations
Box-Cox
choropleth maps
Color
color binning
color mapping
Communities
data preconditioning
Data transformation
data visualisation
Data visualization
Gaussian distribution
Histograms
Hospitals
Image color analysis
improved visual encoding
inference mechanisms
normal distribution
Preconditioning
statistical analysis
statistical community
statistical inference procedures
statistical modeling
time series
time-series scaling
Transformations
Transforms
Visual
Visualization
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Summary:The concept of preconditioning data (utilizing a power transformation as an initial step) for analysis and visualization is well established within the statistical community and is employed as part of statistical modeling and analysis. Such transformations condition the data to various inherent assumptions of statistical inference procedures, as well as making the data more symmetric and easier to visualize and interpret. In this paper, we explore the use of the Box-Cox family of power transformations to semiautomatically adjust visual parameters. We focus on time-series scaling, axis transformations, and color binning for choropleth maps. We illustrate the usage of this transformation through various examples, and discuss the value and some issues in semiautomatically using these transformations for more effective data visualization.
ISSN:1077-2626
1941-0506
DOI:10.1109/TVCG.2012.64