Fuzzy linear discriminant analysis clustering with its application
Many fuzzy clustering are based on within-cluster scatter with a compactness measure , but in this paper explaining new fuzzy clustering method which depend on within-cluster scatter with a compactness measure and between-cluster scatter with a separation measure called the fuzzy compactness and sep...
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Veröffentlicht in: | Iraqi journal of science 2013, Vol.54 (3), p.739-743 |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | ara ; eng |
Online-Zugang: | Volltext |
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Zusammenfassung: | Many fuzzy clustering are based on within-cluster scatter with a compactness
measure , but in this paper explaining new fuzzy clustering method which depend on
within-cluster scatter with a compactness measure and between-cluster scatter with a
separation measure called the fuzzy compactness and separation (FCS). The fuzzy
linear discriminant analysis (FLDA) based on within-cluster scatter matrix and
between-cluster scatter matrix . Then two fuzzy scattering matrices in the objective
function assure the compactness between data elements and cluster centers .To test
the optimal number of clusters using validation clustering method is discuss .After
that an illustrate example are applied. |
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ISSN: | 0067-2904 2312-1637 |