[
https://issues.apache.org/jira/browse/SPARK-17311?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sean Owen updated SPARK-17311:
------------------------------
Issue Type: Improvement (was: Bug)
> Standardize Python-Java MLlib API to accept optional long seeds in all cases
> ----------------------------------------------------------------------------
>
> Key: SPARK-17311
> URL: https://issues.apache.org/jira/browse/SPARK-17311
> Project: Spark
> Issue Type: Improvement
> Components: MLlib, PySpark
> Affects Versions: 2.0.0
> Reporter: Sean Owen
> Assignee: Sean Owen
> Priority: Minor
> Fix For: 2.1.0
>
>
> (Note this follows on https://issues.apache.org/jira/browse/SPARK-16832 )
> There are a few seed-related issues in the Pyspark-MLLib bridge:
> - {{PythonMLlibAPI}} methods that take a seed don't always take a
> {{java.lang.Long}} consistently, allowing the Python API to specify "no seed"
> - .mllib's {{Word2VecModel}} seems to be an odd man out in .mllib in that it
> picks its own random seed. Instead it should default to None, meaning,
> letting the Scala implementation pick a seed
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
