[jira] [Commented] (SPARK-14450) Python OneVsRest should train multiple models at once
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https://issues.apache.org/jira/browse/SPARK-14450?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16047245#comment-16047245
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Joseph K. Bradley commented on SPARK-14450:
---
See linked JIRA for new issue.
> Python OneVsRest should train multiple models at once
> -
>
> Key: SPARK-14450
> URL: https://issues.apache.org/jira/browse/SPARK-14450
> Project: Spark
> Issue Type: Improvement
> Components: ML, PySpark
>Reporter: Joseph K. Bradley
>
> [SPARK-7861] adds a Python wrapper for OneVsRest. Because of possible issues
> related to using existing libraries like {{multiprocessing}}, we are not
> training multiple models in parallel initially.
> This issue is for prototyping, testing, and implementing a way to train
> multiple models at once. Speaking with [~joshrosen], a good option might be
> the concurrent.futures package:
> * Python 3.x:
> [https://docs.python.org/3/library/concurrent.futures.html#module-concurrent.futures]
> * Python 2.x: [https://pypi.python.org/pypi/futures]
> We will *not* add this for Spark 2.0, but it will be good to investigate for
> 2.1.
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[jira] [Commented] (SPARK-14450) Python OneVsRest should train multiple models at once
[
https://issues.apache.org/jira/browse/SPARK-14450?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16047244#comment-16047244
]
Joseph K. Bradley commented on SPARK-14450:
---
Scala already has parallelization. I just rediscovered this issue...so I'll
close this old copy.
> Python OneVsRest should train multiple models at once
> -
>
> Key: SPARK-14450
> URL: https://issues.apache.org/jira/browse/SPARK-14450
> Project: Spark
> Issue Type: Improvement
> Components: ML, PySpark
>Reporter: Joseph K. Bradley
>
> [SPARK-7861] adds a Python wrapper for OneVsRest. Because of possible issues
> related to using existing libraries like {{multiprocessing}}, we are not
> training multiple models in parallel initially.
> This issue is for prototyping, testing, and implementing a way to train
> multiple models at once. Speaking with [~joshrosen], a good option might be
> the concurrent.futures package:
> * Python 3.x:
> [https://docs.python.org/3/library/concurrent.futures.html#module-concurrent.futures]
> * Python 2.x: [https://pypi.python.org/pypi/futures]
> We will *not* add this for Spark 2.0, but it will be good to investigate for
> 2.1.
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[jira] [Commented] (SPARK-14450) Python OneVsRest should train multiple models at once
[
https://issues.apache.org/jira/browse/SPARK-14450?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15653309#comment-15653309
]
fanlu commented on SPARK-14450:
---
Why scala version does not need to use parallelization
> Python OneVsRest should train multiple models at once
> -
>
> Key: SPARK-14450
> URL: https://issues.apache.org/jira/browse/SPARK-14450
> Project: Spark
> Issue Type: Improvement
> Components: ML, PySpark
>Reporter: Joseph K. Bradley
>
> [SPARK-7861] adds a Python wrapper for OneVsRest. Because of possible issues
> related to using existing libraries like {{multiprocessing}}, we are not
> training multiple models in parallel initially.
> This issue is for prototyping, testing, and implementing a way to train
> multiple models at once. Speaking with [~joshrosen], a good option might be
> the concurrent.futures package:
> * Python 3.x:
> [https://docs.python.org/3/library/concurrent.futures.html#module-concurrent.futures]
> * Python 2.x: [https://pypi.python.org/pypi/futures]
> We will *not* add this for Spark 2.0, but it will be good to investigate for
> 2.1.
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