Skip to content

derrickburns/generalized-kmeans-clustering

Repository files navigation

Generalized K-Means Clustering

This project generalizes the Spark MLLIB Batch K-Means (v1.1.0) clusterer and the Spark MLLIB Streaming K-Means (v1.2.0) clusterer. Most practical variants of K-means clustering are implemented or can be implemented with this package, including:

If you find a novel variant of k-means clustering that is provably superior in some manner, implement it using the package and send a pull request along with the paper analyzing the variant!

This code has been tested on data sets of tens of millions of points in a 700+ dimensional space using a variety of distance functions. Thanks to the excellent core Spark implementation, it rocks!

About

Spark library for generalized K-Means clustering. Supports general Bregman divergences. Suitable for clustering probabilistic data, time series data, high dimensional data, and very large data.

Topics

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Contributors 4

  •  
  •  
  •  
  •  

Languages