Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/14956#discussion_r77880357
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala
---
@@ -395,7 +395,7 @@ object PowerIterationClustering extends Logging {
val points = v.mapValues(x => Vectors.dense(x)).cache()
val model = new KMeans()
.setK(k)
- .setSeed(0L)
+ .setSeed(5L)
--- End diff --
The desired test result here depends on the seed, since some random
initializations don't happen to produce the clustering that the test has in
mind. 0 no longer worked after the change above but 5 did. This does indicate
the clustering is different. Yes that sounds like a good quick science
experiment, to verify more empirically that the clustering results here match
what the paper advertises.
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