Erik,
Thank you for your answer. It seems really good, but unfortunately I'm
not very familiar with Scala, so I have partly understood.
Could you please explain your idea with Spark implementation?
Best regards,
Marko
On Mon 01 Jun 2015 06:35:17 PM CEST, Erik Erlandson wrote:
I haven't given any thought to streaming it, but in case it's useful I do have
a k-medoids implementation for Spark:
http://silex.freevariable.com/latest/api/#com.redhat.et.silex.cluster.KMedoids
Also a blog post about multi-threading it:
http://erikerlandson.github.io/blog/2015/05/06/parallel-k-medoids-using-scala-parseq/
----- Original Message -----
Hello everyone,
I have an idea and I would like to get a validation from community about
it.
In Mahout there is an implementation of Streaming K-means. I'm
interested in your opinion would it make sense to make a similar
implementation of Streaming K-medoids?
K-medoids has even bigger problems than K-means because it's not
scalable, but can be useful in some cases (e.g. It allows more
sophisticated distance measures).
What is your opinion about such an approach? Does anyone see problems
with it?
Best regards,
Marko
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