Visual analysis based on algorithmic classification

Author

Johansson, J. ; Jern, M. ; Treloar, R. ; Jansson, M.

Author_Institution

ITN, Linkoping Univ., Sweden

fYear

2003

fDate

16-18 July 2003

Firstpage

86

Lastpage

93

Abstract

Extracting actionable insight from large high dimensional data sets, and its use for more effective decision-making, has become a pervasive problem across many fields in research and industry. We describe an investigation of the application of tightly coupled statistical and visual analysis techniques to this task. The approach we choose is "unsupervised learning" where we investigate the advantages offered by close coupling of the self-organizing map algorithm with new combinations of visualization components and techniques for interactivity.

Keywords

data analysis; data mining; data visualisation; decision making; graphical user interfaces; interactive systems; self-organising feature maps; statistical analysis; unsupervised learning; very large databases; knowledge discovery; self-organizing map algorithm; tightly coupled visualization; unsupervised learning; visual analysis; visual user interface; Algorithm design and analysis; Books; Classification algorithms; Data mining; Data visualization; Decision making; Mathematical model; Neural networks; Unsupervised learning; User interfaces;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Visualization, 2003. IV 2003. Proceedings. Seventh International Conference on

Print_ISBN

0-7695-1988-1

Type

conf

DOI

10.1109/IV.2003.1217962

Filename

1217962