Publication | Closed Access
New results in fuzzy clustering based on the concept of indistinguishability relation
22
Citations
4
References
1988
Year
New ResultsFuzzy LogicFuzzy SystemsClustering (Nuclear Physics)Data ScienceData MiningEngineeringFuzzy ComputingFuzzy MathematicsFuzzy ClusteringFuzzy R-clusterCluster ValidityFuzzy OptimizationFuzzy Pattern RecognitionFuzzy CoverageClustering (Data Mining)StatisticsIndistinguishability Relation
The issue of validity in clustering is considered and a definition of fuzzy r-cluster that extends E. Ruspini's definition (1982) is proposed. This definition is based on an indistinguishability relation based on the concept of t-norm. The fuzzy r-cluster's metrical properties are studied through the dual concept of t-conorm that leads to G-pseudometrics. From the concept of G-pseudometric, fuzzy r-clusters and fuzzy cluster coverages are defined. The authors propose a measure of cluster validity based on the concept of fuzzy coverage. The basic idea of the approach presented is that the smaller the difference between the degrees of membership and the degrees of indistinguishability, the better the clustering.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
| Year | Citations | |
|---|---|---|
Page 1
Page 1