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Cluster analysis based on dimensional information with applications to feature selection and classificationA new clustering algorithm is presented that is based on dimensional information. The algorithm includes an inherent feature selection criterion, which is discussed. Further, a heuristic method for choosing the proper number of intervals for a frequency distribution histogram, a feature necessary for the algorithm, is presented. The algorithm, although usable as a stand-alone clustering technique, is then utilized as a global approximator. Local clustering techniques and configuration of a global-local scheme are discussed, and finally the complete global-local and feature selector configuration is shown in application to a real-time adaptive classification scheme for the analysis of remote sensed multispectral scanner data.
Document ID
19740047845
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Eigen, D. J.
(Bell Telephone Laboratories, Inc. Piscataway, N.J., United States)
Fromm, F. R.
(Bell Telephone Laboratories, Inc. Naperville, Ill., United States)
Northouse, R. A.
(Wisconsin, University Milwaukee, Wis., United States)
Date Acquired
August 7, 2013
Publication Date
May 1, 1974
Subject Category
Computers
Accession Number
74A30595
Funding Number(s)
CONTRACT_GRANT: NAS9-12931
Distribution Limits
Public
Copyright
Other

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