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Recent convergence results for the fuzzy c-means clustering algorithms
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-1-4757-0450-1openalex-snapshot
Pattern Recognition with Fuzzy Objective Function Algorithms
inferredcites →https://doi.org/10.1007/bf00940196openalex-snapshot
Local convergence analysis of a grouped variable version of coordinate descent
inferredcites →https://doi.org/10.1016/0031-3203(86)90047-6openalex-snapshot
Local convergence of the fuzzy c-Means algorithms
inferredcites →https://doi.org/10.1016/0031-3203(86)90048-8openalex-snapshot
Fuzzy c-means: Optimality of solutions and effective termination of the algorithm
inferredcites →https://doi.org/10.1016/0167-8655(85)90012-1openalex-snapshot
Parametric estimation for normal mixtures
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Parameter estimation for finite mixture distributions
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A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters
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On the asymptotic properties of fuzzy c-means cluster prototypes as estimators of mixture subpopulation centers
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A Convergence Theorem for the Fuzzy ISODATA Clustering Algorithms
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On the Local Optimality of the Fuzzy Isodata Clustering Algorithm
inferredcites →https://doi.org/10.1109/tsmc.1987.6499296openalex-snapshot
Convergence theory for fuzzy c-means: Counterexamples and repairs
inferredcites →https://doi.org/10.1207/s15327906mbr0503_6openalex-snapshot
PATTERN CLUSTERING BY MULTIVARIATE MIXTURE ANALYSIS
inferredcites →https://doi.org/10.2307/1909424openalex-snapshot
Nonlinear Programming: A Unified Approach
inferredcites →https://doi.org/10.2307/2343701openalex-snapshot
Nonlinear Programming: A Unified Approach.
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