Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Visual Classification

  • Mihael AnkerstEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_1123


Cooperative classification


Decision trees have been successfully used for the task of classification. However, state-of the-art algorithms do not incorporate the user in the tree construction process. Through the involvement of the user in the process of classification, he/she can provide domain knowledge to focus the search of the algorithm and gain a deeper understanding of the resulting decision tree. In a cooperative approach, both the user and the computer contribute what they do best: the user specifies the task, focuses the search using his/her domain knowledge, and evaluates the (intermediate) results of the algorithm. The computer, on the other hand, automatically creates patterns satisfying the specified user constraints. The cooperative approach is based on a novel visualization technique for multidimensional data representing their impurity with respect to their class labels.

Historical Background

The idea of visual classification has been built upon...

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Recommended Reading

  1. 1.
    Ankerst M, Elsen C, Ester M, Kriegel H-P. Visual classification: an interactive approach to decision tree construction. In: Proceedings of the 5th International Conference on Knowledge Discovery and Data; 1999. p. 392–6.Google Scholar
  2. 2.
    Ankerst M, Ester M, Kriegel HP Towards an effective cooperation of the computer and the user for classification. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; 2000.Google Scholar
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    Breiman L, Friedman JH, Olshen RA, Stone PJ. Classification and regression trees. Belmont: Wadsworth International Group; 1984.zbMATHGoogle Scholar
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    Keim DA Visual database exploration techniques. Tutorial at International Conference on Knowledge Discovery and Data Mining; 1997.Google Scholar
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    Mehta M, Agrawal R, Rissanen J SLIQ: a fast scalable classifier for data mining. In: Advances in Database Technology, Proceedings of the 5th International Conference on Extending Database Technology; 1996.Google Scholar
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    Michie D, Spiegelhalter DJ, Taylor CC. Machine learning, neural and statistical classification. New York: Ellis Horwood; 1994. See also http://www.ncc.up.pt/liacc/ML/statlog/datasets.html

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Ludwig-Maximilians-Universität MünchenMunichGermany

Section editors and affiliations

  • Daniel A. Keim
    • 1
  1. 1.Computer Science DepartmentUniversity of KonstanzKonstanzGermany