Github user mengxr commented on a diff in the pull request: https://github.com/apache/spark/pull/4254#discussion_r23876362 --- Diff: docs/mllib-clustering.md --- @@ -34,6 +34,26 @@ a given dataset, the algorithm returns the best clustering result). * *initializationSteps* determines the number of steps in the k-means\|\| algorithm. * *epsilon* determines the distance threshold within which we consider k-means to have converged. +### Power Iteration Clustering + +Power iteration clustering is a scalable and efficient algorithm for clustering points given pointwise mutual affinity values. Internally the algorithm: + +* accepts a [Graph](https://spark.apache.org/docs/0.9.2/api/graphx/index.html#org.apache.spark.graphx.Graph) that represents a normalized pairwise affinity between all input points. +* calculates the principal eigenvalue and eigenvector +* Clusters each of the input points according to their principal eigenvector component value + +Details of this algorithm are found within [Power Iteration Clustering, Lin and Cohen]{www.icml2010.org/papers/387.pdf} --- End diff -- This is not the correct syntax for links in markdown. Use `[](...)`
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