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https://issues.apache.org/jira/browse/SPARK-7131?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng resolved SPARK-7131.
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Resolution: Fixed
Fix Version/s: 1.5.0
Issue resolved by pull request 7294
[https://github.com/apache/spark/pull/7294]
> Move tree,forest implementation from spark.mllib to spark.ml
> ------------------------------------------------------------
>
> Key: SPARK-7131
> URL: https://issues.apache.org/jira/browse/SPARK-7131
> Project: Spark
> Issue Type: Improvement
> Components: ML, MLlib
> Affects Versions: 1.4.0
> Reporter: Joseph K. Bradley
> Assignee: Joseph K. Bradley
> Fix For: 1.5.0
>
> Original Estimate: 168h
> Remaining Estimate: 168h
>
> We want to change and improve the spark.ml API for trees and ensembles, but
> we cannot change the old API in spark.mllib. To support the changes we want
> to make, we should move the implementation from spark.mllib to spark.ml. We
> will generalize and modify it, but will also ensure that we do not change the
> behavior of the old API.
> This JIRA should be done in several PRs, in this order:
> 1. Copy the implementation over to spark.ml and change the spark.ml classes
> to use that implementation, rather than calling the spark.mllib
> implementation. The current spark.ml tests will ensure that the 2
> implementations learn exactly the same models. Note: This should include
> performance testing to make sure the updated code does not have any
> regressions.
> 2. Remove the spark.mllib implementation, and make the spark.mllib APIs
> wrappers around the spark.ml implementation. The spark.ml tests will again
> ensure that we do not change any behavior.
> 3. Move the unit tests to spark.ml, and change the spark.mllib unit tests to
> verify model equivalence.
> After these updates, we can more safely generalize and improve the spark.ml
> implementation.
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