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Posted to issues@spark.apache.org by "Seth Hendrickson (JIRA)" <ji...@apache.org> on 2016/03/03 23:05:19 UTC
[jira] [Comment Edited] (SPARK-13066) Specify types for
per-model/estimator params in ML to allow automatic type conversion
[ https://issues.apache.org/jira/browse/SPARK-13066?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15178693#comment-15178693 ]
Seth Hendrickson edited comment on SPARK-13066 at 3/3/16 10:05 PM:
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Hey [~josephkb], [SPARK-13068|https://issues.apache.org/jira/browse/SPARK-13068] proposes a solution to this problem by making the Python params more like Scala params, which accept as input a validation function. I submitted a PR for it here [SPARK-13068|https://github.com/apache/spark/pull/11099]. I chatted with [~holdenk] on this and we arrived on it as a more flexible type conformance mechanism in python. If you get a chance, I'd love feedback on the approach.
was (Author: sethah):
Hey [~josephkb], [SPARK-13068|https://issues.apache.org/jira/browse/SPARK-13068] proposes a solution to this problem by making the Python params more like Scala params, which accept as input a validation function. I submitted a PR for it here [SPARK-13068|https://github.com/apache/spark/pull/11099]. I chatted with @holdenk on this and we arrived on it as a more flexible type conformance mechanism in python. If you get a chance, I'd love feedback on the approach.
> Specify types for per-model/estimator params in ML to allow automatic type conversion
> -------------------------------------------------------------------------------------
>
> Key: SPARK-13066
> URL: https://issues.apache.org/jira/browse/SPARK-13066
> Project: Spark
> Issue Type: Improvement
> Components: ML, PySpark
> Reporter: holdenk
> Priority: Minor
>
> Specify types for per-model/estimator params in the same format as done for generate params in SPARK-7675 now that SPARK-10509 is merged in and we won't need to duplicate it everywhere.
> cc [~sethah] who chatted with about this
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