♣ FT Data Mining and Other Applications

Alfred Inselberg ()
Additional contact information
Alfred Inselberg: Tel Aviv University School of Mathematical Sciences

Chapter 10 in Parallel Coordinates, 2009, pp 379-427 from Springer

Abstract: 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 2 M subsets, 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.

Keywords: Data Mining; Data Item; Hamiltonian Path; Exploratory Data Analysis; Automatic Transmission (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-0-387-68628-8_10

Ordering information: This item can be ordered from
http://www.springer.com/9780387686288

DOI: 10.1007/978-0-387-68628-8_10

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().