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# 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} }

- Published 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