Abstract
The first, and still most popular, application of parallel coordinates is in exploratory data analysis (EDA) to discover data subsets (relations) that fulfill certain objectives and guide the formulation of hypotheses. A data set with Mitems has 2Msubsets, any one of which may be the one we really want. With a good data display, our fantastic pattern-recognition ability cannot only cut great swaths in our search through this combinatorial explosion, but also extract insights from the visual patterns. These are the core reasons for data visualization.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2009 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Inselberg, A. (2009). ♣ FT Data Mining and Other Applications. In: Parallel Coordinates. Springer, New York, NY. https://doi.org/10.1007/978-0-387-68628-8_10
Download citation
DOI: https://doi.org/10.1007/978-0-387-68628-8_10
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-21507-5
Online ISBN: 978-0-387-68628-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)