[
https://issues.apache.org/jira/browse/SPARK-13490?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Yanbo Liang updated SPARK-13490:
--------------------------------
Description: Like SPARK-13132 for LogisticRegression, LinearRegression with
L1 regularization should also cache the value of the standardization rather
than re-fetching it from the ParamMap for every OWLQN iteration. (was: Like
SPARK-13132 for LogisticRegression, when LinearRegression with L1
regularization, the inner functor passed to the quasi-newton optimizer in
{{org.apache.spark.ml.regression.LinearRegression#train}} makes repeated calls
to {{$(standardization)}}. This ultimately involves repeated string
interpolation triggered by {{org.apache.spark.ml.param.Param#hashCode}}. We
should cache the value of the standardization rather than re-fetching it from
the ParamMap for every iteration.)
> ML LinearRegression should cache standardization param value
> ------------------------------------------------------------
>
> Key: SPARK-13490
> URL: https://issues.apache.org/jira/browse/SPARK-13490
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Reporter: Yanbo Liang
> Priority: Minor
>
> Like SPARK-13132 for LogisticRegression, LinearRegression with L1
> regularization should also cache the value of the standardization rather than
> re-fetching it from the ParamMap for every OWLQN iteration.
--
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
