Generalized K-Means Clustering
  • Introduction
    • Relation to Spark K-Means Clusterer
    • Algorithms Implemented
  • Requirements
  • Quick Start
  • Concepts
    • Bregman Divergence
    • WeightedVector
    • BregmanPoint, BregmanCenter, BregmanPointOps
    • KMeansModel
    • MultiKMeansClusterer
    • KMeansSelector
  • Usage
    • Selecting a Distance Function
    • Constructing K-Means Models using Clusterers
    • Embedding Data
    • Seeding the Set of Cluster Centers
    • Iterative Clustering
    • Alternative KMeansModel Construction
    • Customizing
      • Creating a Custom Distance Function
      • Creating a Custom Embedding
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Concepts

PreviousQuick StartNextBregman Divergence
Bregman Divergence
WeightedVector
BregmanPoint, BregmanCenter, BregmanPointOps
KMeansModel
MultiKMeansClusterer
KMeansSelector