Ítem
| Clara i Lloret, Narcís | |
| agost 2007 | |
| Our purpose is to provide a set-theoretical frame to clustering fuzzy relational data basically based on cardinality of the fuzzy subsets that represent objects and their complementaries, without applying any crisp property. From this perspective we define a family of fuzzy similarity indexes which includes a set of fuzzy indexes introduced by Tolias et al, and we analyze under which conditions it is defined a fuzzy proximity relation. Following an original idea due to S. Miyamoto we evaluate the similarity between objects and features by means the same mathematical procedure. Joining these concepts and methods we establish an algorithm to clustering fuzzy relational data. Finally, we present an example to make clear all the process | |
| application/pdf | |
| Clara, N. (2007). A Homogeneous Set-Theoretical Frame for Clustering Fuzzy Relational Data. Fourth International Conference on Fuzzy Systems and Knowledge Discovery : 2007 : FSKD 2007, 1, 712 - 716. Recuperat 28 setembre 2010, a http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4406016 | |
| 978-0-7695-2874-8 | |
| http://hdl.handle.net/10256/3059 | |
| eng | |
| IEEE | |
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Reproducció digital del document publicat a: http://dx.doi.org/10.1109/FSKD.2007.44 Articles publicats (D-IMA) |
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| © Fourth International Conference on Fuzzy Systems and Knowledge Discovery : 2007 : FSKD 2007, 2007, vol. 1, p. 712-716 | |
| Tots els drets reservats | |
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Conjunts borrosos
Conjunts, Teoria de Sistemes borrosos Fuzzy sets Set theory |
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| A Homogeneous Set-Theoretical Frame for Clustering Fuzzy Relational Data | |
| info:eu-repo/semantics/article | |
| DUGiDocs |
