Soft clustering of multidimensional data: A semi-fuzzy approach

DOI10.1016/0031-3203(84)90054-2zbMath0542.62048OpenAlexW2066009341MaRDI QIDQ795446

N. E. Zubov

Publication date: 1984

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

Full work available at URL: https://doi.org/10.1016/0031-3203(84)90054-2

zbMATH Keywords

multidimensional dataclustering modelsfuzzy ISODATA algorithmfuzzy pattern recognitionsemi-fuzzy classificationunsupervised fuzzy classification

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Pattern recognition, speech recognition (68T10)

Related Items (6)

Multidimensional data clustering utilizing hybrid search strategies ⋮ A robust fuzzy \(k\)-means clustering model for interval valued data ⋮ Advances in theory and applications of fuzzy clustering ⋮ A new method to estimate null values in relational database systems based on automatic clustering techniques ⋮ Fuzzy clustering of time series in the frequency domain ⋮ A distance-relatedness dynamic model for clustering high dimensional data of arbitrary shapes and densities

Cites Work

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• Numerical taxonomy with fuzzy sets
• Numerical methods for fuzzy clustering
• A Convergence Theorem for the Fuzzy ISODATA Clustering Algorithms
• A Graph Theoretic Analysis of Pattern Classification via Tamura's Fuzzy Relation
• Well-Separated Clusters and Optimal Fuzzy Partitions
• Some Recent Investigations of a New Fuzzy Partitioning Algorithm and its Application to Pattern Classification Problems
• Fuzzy sets
• A new approach to clustering
• A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters

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