[jira] [Commented] (SPARK-17241) SparkR spark.glm should have configurable regularization parameter
[ https://issues.apache.org/jira/browse/SPARK-17241?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15444279#comment-15444279 ] Apache Spark commented on SPARK-17241: -- User 'keypointt' has created a pull request for this issue: https://github.com/apache/spark/pull/14856 > SparkR spark.glm should have configurable regularization parameter > -- > > Key: SPARK-17241 > URL: https://issues.apache.org/jira/browse/SPARK-17241 > Project: Spark > Issue Type: Improvement >Reporter: Junyang Qian > > Spark has configurable L2 regularization parameter for generalized linear > regression. It is very important to have them in SparkR so that users can run > ridge regression. -- 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
[jira] [Commented] (SPARK-17241) SparkR spark.glm should have configurable regularization parameter
[ https://issues.apache.org/jira/browse/SPARK-17241?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15437717#comment-15437717 ] Junyang Qian commented on SPARK-17241: -- I'll take a closer look and see if we can add it easily. > SparkR spark.glm should have configurable regularization parameter > -- > > Key: SPARK-17241 > URL: https://issues.apache.org/jira/browse/SPARK-17241 > Project: Spark > Issue Type: Improvement >Reporter: Junyang Qian > > Spark has configurable L2 regularization parameter for generalized linear > regression. It is very important to have them in SparkR so that users can run > ridge regression. -- 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
[jira] [Commented] (SPARK-17241) SparkR spark.glm should have configurable regularization parameter
[ https://issues.apache.org/jira/browse/SPARK-17241?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15437692#comment-15437692 ] Junyang Qian commented on SPARK-17241: -- [~shivaram] It seems that spark has it for linear regression but not for glm. > SparkR spark.glm should have configurable regularization parameter > -- > > Key: SPARK-17241 > URL: https://issues.apache.org/jira/browse/SPARK-17241 > Project: Spark > Issue Type: Improvement >Reporter: Junyang Qian > > Spark has configurable L2 regularization parameter for generalized linear > regression. It is very important to have them in SparkR so that users can run > ridge regression. -- 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
[jira] [Commented] (SPARK-17241) SparkR spark.glm should have configurable regularization parameter
[ https://issues.apache.org/jira/browse/SPARK-17241?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15437588#comment-15437588 ] Xin Ren commented on SPARK-17241: - I can work on this one :) > SparkR spark.glm should have configurable regularization parameter > -- > > Key: SPARK-17241 > URL: https://issues.apache.org/jira/browse/SPARK-17241 > Project: Spark > Issue Type: Improvement >Reporter: Junyang Qian > > Spark has configurable L2 regularization parameter for generalized linear > regression. It is very important to have them in SparkR so that users can run > ridge regression. -- 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
[jira] [Commented] (SPARK-17241) SparkR spark.glm should have configurable regularization parameter
[ https://issues.apache.org/jira/browse/SPARK-17241?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15437536#comment-15437536 ] Shivaram Venkataraman commented on SPARK-17241: --- +1 - This would be good to have. Also on a related note is it hard to get elasticnet working in spark.glm ? We can create a new JIRA for it if all we need is a new wrapper. > SparkR spark.glm should have configurable regularization parameter > -- > > Key: SPARK-17241 > URL: https://issues.apache.org/jira/browse/SPARK-17241 > Project: Spark > Issue Type: Improvement >Reporter: Junyang Qian > > Spark has configurable L2 regularization parameter for generalized linear > regression. It is very important to have them in SparkR so that users can run > ridge regression. -- 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
