[
https://issues.apache.org/jira/browse/SPARK-12326?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sean Owen resolved SPARK-12326.
-------------------------------
Resolution: Done
> Move GBT implementation from spark.mllib to spark.ml
> ----------------------------------------------------
>
> Key: SPARK-12326
> URL: https://issues.apache.org/jira/browse/SPARK-12326
> Project: Spark
> Issue Type: Improvement
> Components: ML, MLlib
> Reporter: Seth Hendrickson
> Assignee: Seth Hendrickson
> Priority: Minor
>
> Several improvements can be made to gradient boosted trees, but are not
> possible without moving the GBT implementation to spark.ml (e.g.
> rawPrediction column, feature importance). This Jira is for moving the
> current GBT implementation to spark.ml, which will have roughly the following
> steps:
> 1. Copy the implementation to spark.ml and change spark.ml classes to use
> that implementation. Current tests will ensure that the implementations learn
> exactly the same models.
> 2. Move the decision tree helper classes over to spark.ml (e.g. Impurity,
> InformationGainStats, ImpurityStats, DTStatsAggregator, etc...). Since
> eventually all tree implementations will reside in spark.ml, the helper
> classes should as well.
> 3. 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.
> 4. Move the unit tests to spark.ml, and change the spark.mllib unit tests to
> verify model equivalence.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
