Shadowed \(c\)-means: integrating fuzzy and rough clustering

DOI10.1016/j.patcog.2009.09.029zbMath1192.68595OpenAlexW2002278745MaRDI QIDQ962669

Witold Pedrycz, Sushmita Mitra, Bishal Barman

Publication date: 7 April 2010

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2009.09.029

zbMATH Keywords

rough setsfuzzy setsthree-valued logiccluster validity indexshadowed sets\(c\)-means algorithm

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10)

Related Items (16)

Adaptive density trajectory cluster based on time and space distance ⋮ Shadowed sets with higher approximation regions ⋮ Three-way decisions of rough vague sets from the perspective of fuzziness ⋮ Relative entropy collaborative fuzzy clustering method ⋮ Rough Classification Based on Correlation Clustering ⋮ Recent fuzzy generalisations of rough sets theory: a systematic review and methodological critique of the literature ⋮ A generalized cost-sensitive model for decision-theoretic three-way approximation of fuzzy sets ⋮ Aggregation operators on shadowed sets ⋮ Shadowed-set-based three-way clustering methods: an investigation of new optimization-based principles ⋮ Semi-supervised shadowed sets for three-way classification on partial labeled data ⋮ Integrating rough set principles in the graded possibilistic clustering ⋮ Constrained three-way approximations of fuzzy sets: from the perspective of minimal distance ⋮ A spatial filtering inspired three-way clustering approach with application to outlier detection ⋮ Improved roughk-means clustering algorithm based on weighted distance measure with Gaussian function ⋮ Principles for constructing three-way approximations of fuzzy sets: a comparative evaluation based on unsupervised learning ⋮ An approach for parameterized shadowed type-2 fuzzy membership functions applied in control applications

Uses Software

• RFCM
• Silhouettes
• clusfind

Cites Work

• Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
• Interval set clustering of web users with rough \(K\)-means
• Some refinements of rough \(k\)-means clustering
• Finding Groups in Data
• Fuzzy Sets and Decisionmaking Approaches in Vowel and Speaker Recognition
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