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An approach to the selection of essential features of objects to be recognized, which is based on sufficient and ε-sufficient statistics, is presented. It is shown how sufficient and ε-sufficient statistics can be used to construct partitions of the space of outcomes of an experiment in order to simplify the pattern recognition process. Whereas the sufficient partitions involve inexactness represented by exact statistical information, the use of ε-sufficient partitions simplifies the decision-making process but at the same time introduces additional inexactness or fuzziness. The relation of ε-sufficient data reduction to fuzzy techniques is shown by defining the grade of membership and the degree of fuzziness in terms of the model introduced
Published in:
Systems, Man and Cybernetics, IEEE Transactions on
(Volume:19
,
Issue:
5
)
Date of Publication: Sep/Oct 1989
- Page(s):
- 1261 - 1263
- ISSN :
- 0018-9472
- INSPEC Accession Number:
- 3606577
- Digital Object Identifier :
- 10.1109/21.44045
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 August 2002
- Issue Date :
- Sep/Oct 1989
- Sponsored by :
- IEEE Systems, Man, and Cybernetics Society
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