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The decision tree classifier - Design and potentialA new classifier has been developed for the computerized analysis of remote sensor data. The decision tree classifier is essentially a maximum likelihood classifier using multistage decision logic. It is characterized by the fact that an unknown sample can be classified into a class using one or several decision functions in a successive manner. The classifier is applied to the analysis of data sensed by Landsat-1 over Kenosha Pass, Colorado. The classifier is illustrated by a tree diagram which for processing purposes is encoded as a string of symbols such that there is a unique one-to-one relationship between string and decision tree.
Document ID
19760035940
Acquisition Source
Legacy CDMS
Document Type
Conference Proceedings
Authors
Hauska, H.
(Purdue Univ. West Lafayette, IN, United States)
Swain, P. H.
(Purdue University West Lafayette, Ind., United States)
Date Acquired
August 8, 2013
Publication Date
January 1, 1975
Subject Category
Cybernetics
Meeting Information
Meeting: Symposium on Machine Processing of Remotely Sensed Data
Location: West Lafayette, IN
Start Date: June 3, 1975
End Date: June 5, 1975
Accession Number
76A18906
Funding Number(s)
CONTRACT_GRANT: NAS9-14016
CONTRACT_GRANT: NAS9-13380
Distribution Limits
Public
Copyright
Other

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