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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