Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/4301#issuecomment-72373979
@viirya If that works better than a randomized vector in general, we can
replace the current initialization. We set it to a random vector to guarantee
that if it far from the first eigenvector. If we want to keep both, instead of
adding new method, we can make the switch an option:
~~~
val pic = new PowerIterationClustering()
.setInitialization("random") // or "degree"
.run(...)
~~~
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