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A survey of decision tree classifier methodologyDecision tree classifiers (DTCs) are used successfully in many diverse areas such as radar signal classification, character recognition, remote sensing, medical diagnosis, expert systems, and speech recognition. Perhaps the most important feature of DTCs is their capability to break down a complex decision-making process into a collection of simpler decisions, thus providing a solution which is often easier to interpret. A survey of current methods is presented for DTC designs and the various existing issues. After considering potential advantages of DTCs over single-state classifiers, subjects of tree structure design, feature selection at each internal node, and decision and search strategies are discussed.
Document ID
19920029711
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Safavian, S. R.
(Purdue Univ. West Lafayette, IN, United States)
Landgrebe, David
(Purdue University West Lafayette, IN, United States)
Date Acquired
August 15, 2013
Publication Date
June 1, 1991
Publication Information
Publication: IEEE Transactions on Systems, Man, and Cybernetics
Volume: 21
ISSN: 0018-9472
Subject Category
Numerical Analysis
Accession Number
92A12335
Funding Number(s)
CONTRACT_GRANT: NAGW-925
CONTRACT_GRANT: NSF ECS-85-07405
Distribution Limits
Public
Copyright
Other

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