Github user mgaido91 commented on the issue:
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kindly ping @dbtsai
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Github user mgaido91 commented on the issue:
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@dbtsai any luck with this? Thanks.
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Github user mgaido91 commented on the issue:
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@dbtsai sure, thanks. Sorry for bothering you. Have a nice vacation!
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Github user dbtsai commented on the issue:
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@mgaido91 I'm on thanksgiving vacation, will be back to community to help
code review on Nov 21st. Sorry for the delay.
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Github user mgaido91 commented on the issue:
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@dbtsai any comments on this? thanks.
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Github user cloud-fan commented on the issue:
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cc @dbtsai
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Github user mgaido91 commented on the issue:
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any more comments on this? Thanks
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Github user mgaido91 commented on the issue:
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thanks @WeichenXu123 , I updated this PR in order to target 3.0.
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Github user WeichenXu123 commented on the issue:
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I think it can target for 3.0. since 2.4 will be released soon and this PR
looks a little complex and need take some time to check carefully.
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Github user mgaido91 commented on the issue:
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as @WeichenXu123 mentioned in
https://github.com/apache/spark/pull/22764#discussion_r228527916, I don't see
other problems with the current PR. The only thing is: do we want to target it
for 2.4
Github user cloud-fan commented on the issue:
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Since this PR is a little more complicated than we expect, we decided to
not have it in 2.4.0. I'm not sure if we can treat it as a special case and put
it in 2.4.1, cc @mengxr
Anyway,
Github user mgaido91 commented on the issue:
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For KMeans we used the ClusteringEvaluator in the examples. Actually, the
training cost is not a good way to evaluate a dataset (the evaluation should be
done on a dataset different from the
Github user cloud-fan commented on the issue:
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does the example need to be updated with this new API?
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Github user mgaido91 commented on the issue:
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cc @cloud-fan @dongjoon-hyun @holdenk @srowen
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