A robust fuzzy k-means clustering model for interval valued data
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DOI: 10.1007/s00180-006-0262-y
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References listed on IDEAS
- D'Urso, Pierpaolo & Giordani, Paolo, 2006. "A weighted fuzzy c-means clustering model for fuzzy data," Computational Statistics & Data Analysis, Elsevier, vol. 50(6), pages 1496-1523, March.
- D'Urso, Pierpaolo & Giordani, Paolo, 2003. "A least squares approach to Principal Component Analysis for interval valued data," Economics & Statistics Discussion Papers esdp03013, University of Molise, Department of Economics.
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Cited by:
- Sinova, Beatriz & Van Aelst, Stefan, 2015. "On the consistency of a spatial-type interval-valued median for random intervals," Statistics & Probability Letters, Elsevier, vol. 100(C), pages 130-136.
- Pierpaolo D’Urso & María Ángeles Gil, 2017. "Fuzzy data analysis and classification," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(4), pages 645-657, December.
- Ferraro, Maria Brigida, 2024. "Fuzzy k-Means: history and applications," Econometrics and Statistics, Elsevier, vol. 30(C), pages 110-123.
- Pierpaolo D’Urso & Riccardo Massari & Livia De Giovanni & Carmela Cappelli, 2017. "Exponential distance-based fuzzy clustering for interval-valued data," Fuzzy Optimization and Decision Making, Springer, vol. 16(1), pages 51-70, March.
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Keywords
Fuzzy k-means; Robust clustering; Interval valued data; Noise center; Noise radius; Noise cluster;All these keywords.
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