spark-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-7780) The intercept in LogisticRegressionWithLBFGS should not be regularized
Date Sun, 24 May 2015 08:07:17 GMT

     [ https://issues.apache.org/jira/browse/SPARK-7780?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-7780:
-----------------------------------

    Assignee:     (was: Apache Spark)

> The intercept in LogisticRegressionWithLBFGS should not be regularized
> ----------------------------------------------------------------------
>
>                 Key: SPARK-7780
>                 URL: https://issues.apache.org/jira/browse/SPARK-7780
>             Project: Spark
>          Issue Type: Bug
>          Components: MLlib
>            Reporter: DB Tsai
>
> The intercept in Logistic Regression represents a prior on categories which should not
be regularized. In MLlib, the regularization is handled through `Updater`, and the `Updater`
penalizes all the components without excluding the intercept which resulting poor training
accuracy with regularization.
> The new implementation in ML framework handles this properly, and we should call the
implementation in ML from MLlib since majority of users are still using MLlib api. 
> Note that both of them are doing feature scalings to improve the convergence, and the
only difference is ML version doesn't regularize the intercept. As a result, when lambda is
zero, they will converge to the same solution.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org


Mime
View raw message