Visualization method and tool for interactive learning of large decision trees

Trong Dung Nguyen; TuBao Ho

doi:10.1117/12.460208

12 March 2002 Visualization method and tool for interactive learning of large decision trees

Trong Dung Nguyen, TuBao Ho

Proceedings Volume 4730, Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV; (2002) https://doi.org/10.1117/12.460208
Event: AeroSense 2002, 2002, Orlando, FL, United States

Abstract

When learning from large datasets, decision tree induction programs often produce very large trees. How to visualize efficiently trees in the learning process, particularly large trees, is still questionable and currently requires efficient tools. This paper presents a visualization method and tool for interactive learning of large decision trees, that includes a new visualization technique called T2.5D (stands for Tress 2.5 Dimensions). After a brief discussion on requirements for tree visualizers and related work, the paper focuses on presenting developing techniques for the issues (1) how to visualize efficiently large decision trees; and (2) how to visualize decision trees in the learning process.

Citation Download Citation

Trong Dung Nguyen and TuBao Ho "Visualization method and tool for interactive learning of large decision trees", Proc. SPIE 4730, Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV, (12 March 2002); https://doi.org/10.1117/12.460208

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