Point Clustering

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Point Clustering: Various Approaches

Please fill this in with any approaches that you have tried for Point Clustering along with code snippets. Please include discussion on why a particular method worked well or didn't work well and what circumstances it may be good for.

Possible Approaches

  • Coordinate interleaving (i.e. 1. rounding input coordinates, 2. grouping/aggregating them, and then 3. averaging their original coordinates so that the cluster position is at the weighted coordinate of all input geometries).
  • K-means Clustering
  • Hierarchical Clustering
  • Distance calculation for each coordinate pair

Input Parameters

Depending on algorithm...

Partitioning methods

  • Map grid width ("quare / manhattan world", see coordinate interleaving/rounding)
  • Some self-correlation threshold (see e.g. k-means)
  • Predefined irregular polygons (e.g. zip code boundaries)

Implementations

References