Simplifying Decision Trees: A Survey

Simplifying Decision Trees: A Survey (1996)

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by Leonard A. Breslow , David W. Aha

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Datum	Value	Source
TITLE	Simplifying Decision Trees: A Survey	user correction - Legacy Corrections
AUTHOR NAME	Leonard A. Breslow	SVM HeaderParse 0.2
AUTHOR AFFIL	Navy Center for Applied Research in Artificial Intelligence; Naval Research Laboratory	SVM HeaderParse 0.2
AUTHOR ADDR	Washington, DC 20375	SVM HeaderParse 0.2
AUTHOR NAME	David W. Aha	SVM HeaderParse 0.2
AUTHOR AFFIL	Navy Center for Applied Research in Artificial Intelligence; Naval Research Laboratory	SVM HeaderParse 0.2
AUTHOR ADDR	Washington, DC 20375	SVM HeaderParse 0.2
ABSTRACT	Induced decision trees are an extensively-researched solution to classification tasks. For many practical tasks, the trees produced by tree-generation algorithms are not comprehensible to users due to their size and complexity. Although many tree induction algorithms have been shown to produce simpler, more comprehensible trees (or data structures derived from trees) with good classification accuracy, tree simplification has usually been of secondary concern relative to accuracy and no attempt has been made to survey the literature from the perspective of simplification. We present a framework that organizes the approaches to tree simplification and summarize and critique the approaches within this framework. The purpose of this survey is to provide researchers and practitioners with a concise overview of tree-simplification approaches and insight into their relative capabilities. In our final discussion, we briefly describe some empirical findings and discuss the application of tree i...	user correction - Legacy Corrections
YEAR	1996	user correction - Legacy Corrections
CITATIONS	142 found	ParsCit 1.0