[
https://issues.apache.org/jira/browse/SPARK-10785?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14986270#comment-14986270
]
holdenk commented on SPARK-10785:
---------------------------------
Do we still want to sample the input? Looking at the previous jira (for
decision trees) - the work was done on a per feature basis and
QuantileDiscretizer only works on a single feature at a time. Or we we want to
extend QuantileDiscretizer to take multiple input columns?
> Scale QuantileDiscretizer using distributed binning
> ---------------------------------------------------
>
> Key: SPARK-10785
> URL: https://issues.apache.org/jira/browse/SPARK-10785
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Reporter: Joseph K. Bradley
>
> [SPARK-10064] improves binning in decision trees by distributing the
> computation. QuantileDiscretizer should do the same.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
