[ https://issues.apache.org/jira/browse/SPARK-18616?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Nick Pentreath updated SPARK-18616: ----------------------------------- Target Version/s: (was: 2.0.2) > Pure Python Implementation of MLWritable for use in Pipeline > ------------------------------------------------------------ > > Key: SPARK-18616 > URL: https://issues.apache.org/jira/browse/SPARK-18616 > Project: Spark > Issue Type: Improvement > Components: ML > Affects Versions: 2.0.2 > Environment: pyspark > Reporter: Andrea Matsunaga > > When developing an estimator and model completely in python, it is possible > to implement the save() function, and it works for a standalone model, but > not when added to a Pipeline. The reason is that Pipeline save implementation > forces the use of JavaMLWritable, thus also requiring the object to have > methods that are meaningful only to Java objects. Pipelines implementation > need to have a check for the type of writable object defined. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org