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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2016/02/25 10:40:18 UTC

[jira] [Commented] (SPARK-13490) ML LinearRegression should cache standardization param value

    [ https://issues.apache.org/jira/browse/SPARK-13490?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15166997#comment-15166997 ] 

Apache Spark commented on SPARK-13490:
--------------------------------------

User 'yanboliang' has created a pull request for this issue:
https://github.com/apache/spark/pull/11367

> 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, 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.



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