PaintingClass: Interactive construction, visualization and exploration of decision trees

Soon Tee Teoh, Kwan-Liu Ma

Research output: Contribution to conferencePaperpeer-review

39 Scopus citations

Abstract

Decision trees are commonly used for classification. We propose to use decision trees not just for classification but also for the wider purpose of knowledge discovery, because visualizing the decision tree can reveal much valuable information in the data. We introduce PaintingClass, a system for interactive construction, visualization and exploration of decision trees. PaintingClass provides an intuitive layout and convenient navigation of the decision tree. PaintingClass also provides the user the means to interactively construct the decision tree. Each node in the decision tree is displayed as a visual projection of the data. Through actual examples and comparison with other classification methods, we show that the user can effectively use PaintingClass to construct a decision tree and explore the decision tree to gain additional knowledge.

Original languageEnglish (US)
Pages667-672
Number of pages6
DOIs
StatePublished - Dec 1 2003
Event9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '03 - Washington, DC, United States
Duration: Aug 24 2003Aug 27 2003

Other

Other9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '03
CountryUnited States
CityWashington, DC
Period8/24/038/27/03

Keywords

  • Classification
  • Decision trees
  • Information visualization
  • Interactive visualization
  • Visual data mining

ASJC Scopus subject areas

  • Software
  • Information Systems

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