PaintingClass: Interactive construction, visualization and exploration of decision trees

Soon Tee Teoh; Kwan-Liu Ma

doi:10.1145/956750.956837

PaintingClass: Interactive construction, visualization and exploration of decision trees

Soon Tee Teoh, Kwan-Liu Ma

Computer Science

Research output: Contribution to conference › Paper › peer-review

40 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 language	English (US)
Pages	667-672
Number of pages	6
DOIs	https://doi.org/10.1145/956750.956837
State	Published - Dec 1 2003
Event	9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '03 - Washington, DC, United States Duration: Aug 24 2003 → Aug 27 2003

Other

Other	9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '03
Country	United States
City	Washington, DC
Period	8/24/03 → 8/27/03

Keywords

Classification
Decision trees
Information visualization
Interactive visualization
Visual data mining

ASJC Scopus subject areas

Software
Information Systems

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10.1145/956750.956837

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title = "PaintingClass: Interactive construction, visualization and exploration of decision trees",

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.",

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AB - 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.

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KW - Decision trees

KW - Information visualization

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KW - Visual data mining

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PaintingClass: Interactive construction, visualization and exploration of decision trees

Abstract

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Keywords

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