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Posted to issues@spark.apache.org by "Vladimir Feinberg (JIRA)" <ji...@apache.org> on 2016/07/26 00:38:20 UTC
[jira] [Created] (SPARK-16728) migrate internal API for MLlib trees
from spark.mllib to spark.ml
Vladimir Feinberg created SPARK-16728:
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Summary: migrate internal API for MLlib trees from spark.mllib to spark.ml
Key: SPARK-16728
URL: https://issues.apache.org/jira/browse/SPARK-16728
Project: Spark
Issue Type: Sub-task
Reporter: Vladimir Feinberg
Currently, spark.ml trees rely on spark.mllib implementations. There are two issues with this:
1. Spark.ML's GBT TreeBoost algorithm requires storing additional information (the previous ensemble's prediction, for instance) inside the TreePoints (this is necessary to have loss-based splits for complex loss functions).
2. The old impurity API only lets you use summary statistics up to the 2nd order. These are useless for several impurity measures and inadequate for others (e.g., absolute loss or huber loss). It needs some renovation.
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