Chapter 2 Accelerating Lloyd ’ s Algorithm for k-Means Clustering

@inproceedings{Hamerly2017Chapter2A,
  title={Chapter 2 Accelerating Lloyd ’ s Algorithm for k-Means Clustering},
  author={Greg Hamerly and Jonathan Drake},
  year={2017}
}
The k-means clustering algorithm, a staple of data mining and unsupervised learning, is popular because it is simple to implement, fast, easily parallelized, and offers intuitive results. Lloyd’s algorithm is the standard batch, hill-climbing approach for minimizing the k-means optimization criterion. It spends a vast majority of its time computing distances between each of the k cluster centers and the n data points. It turns out that much of this work is unnecessary, because points usually… CONTINUE READING

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