Title :
Visual analysis based on algorithmic classification
Author :
Johansson, J. ; Jern, M. ; Treloar, R. ; Jansson, M.
Author_Institution :
ITN, Linkoping Univ., Sweden
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;
Conference_Titel :
Information Visualization, 2003. IV 2003. Proceedings. Seventh International Conference on
Print_ISBN :
0-7695-1988-1
DOI :
10.1109/IV.2003.1217962
