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Interactive Visualization in Mining Large Decision Trees

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Knowledge Discovery and Data Mining. Current Issues and New Applications (PAKDD 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1805))

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Abstract

This paper presents a tree visualizer that combines several techniques from the field of information visualization to handle efficiently large decision trees in an interactive mining system.

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References

  1. Ankerst, M., Elsen, C, Ester, M., Kriegel, H. P.: Visual Classification: An Interactive Approach to Decision Tree Construction. Proc. of Fifth, Inter. Conf. on Knowledge Discovery and Data Mining (1999), 392–397.

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  3. Card, S., Mackinlay, J., Shneiderman B.: Readings in Information Visualization: Using Vision To Think, Morgan Kaufmann Publishers, Inc. (1999).

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  4. Nguyen, D. T., Ho, T. B.: An Interactive-Graphic System for Decision Tree Induction. Journal of Japanese Society for Artificial Intelligence, Vol. 14 (1999) 131–138.

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  5. Rao, J. S., Potts, W. J. E.: Visualizing Bagged Decision Trees. Proc. of Third Inter. Conf. on Knowledge Discovery and Data Mining, AAAI Press (1997) 243–246.

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Author information

Authors and Affiliations

  1. Japan Advanced Institute of Science and Technology, Tatsunokuchi, Ishikawa, 923-1292, Japan

    Trong Dung Nguyen, Tu Bao Ho & Hiroshi Shimodaira

Authors
  1. Trong Dung Nguyen
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  2. Tu Bao Ho
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  3. Hiroshi Shimodaira
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Editor information

Editors and Affiliations

  1. Graduate School of Systems Management, Universiy of Tsukuba, 3-29-1 Otsuka, Bunkyo-ku, Tokyo, 112-0012, Japan

    Takao Terano

  2. Department of Computer Science and Engineering, Arizona State University, P.O. Box 875 406, Tempe, AZ, 85287-5406

    Huan Liu

  3. Department of Computer Science, National Tsing Hua University, Hsinchu, 300, Taiwan ROC

    Arbee L. P. Chen

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© 2000 Springer-Verlag Berlin Heidelberg

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Nguyen, T.D., Ho, T.B., Shimodaira, H. (2000). Interactive Visualization in Mining Large Decision Trees. In: Terano, T., Liu, H., Chen, A.L.P. (eds) Knowledge Discovery and Data Mining. Current Issues and New Applications. PAKDD 2000. Lecture Notes in Computer Science(), vol 1805. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45571-X_40

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  • DOI: https://doi.org/10.1007/3-540-45571-X_40

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67382-8

  • Online ISBN: 978-3-540-45571-4

  • eBook Packages: Springer Book Archive

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