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Summary

  • Probability Model-Based Clustering
    • Fuzzy clustering
    • Probability-model-based clustering
    • The EM algorithm
  • Clustering High-Dimensional Data
    • Subspace clustering: bi-clustering methods
    • Dimensionality reduction: Spectral clustering
  • Clustering Graphs and Network Data
    • Graph clustering: min-cut vs. sparsest cut
    • High-dimensional clustering methods
    • Graph-specific clustering methods, e.g., SCAN
  • Clustering with Constraints
    • Constraints on instance objects, e.g., Must link vs. Cannot Link
    • Constraint-based clustering algorithms

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