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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2018/11/26 16:30:00 UTC
[jira] [Commented] (SPARK-26173) Prior regularization for Logistic
Regression
[ https://issues.apache.org/jira/browse/SPARK-26173?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16699237#comment-16699237 ]
Apache Spark commented on SPARK-26173:
--------------------------------------
User 'elfausto' has created a pull request for this issue:
https://github.com/apache/spark/pull/23146
> Prior regularization for Logistic Regression
> --------------------------------------------
>
> Key: SPARK-26173
> URL: https://issues.apache.org/jira/browse/SPARK-26173
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Affects Versions: 2.4.0
> Reporter: Facundo Bellosi
> Priority: Minor
>
> This feature enables Maximum A Posteriori (MAP) optimization for Logistic Regression based on a Gaussian prior. In practice, this is just implementing a more general form of L2 regularization parameterized by a (multivariate) mean and precisions vectors. Prior Regularization is enabled when both vectors are provided and regParam > 0 and elasticNetParam < 1.
> Reference: Bishop, Christopher M. (2006). _Pattern Recognition and Machine Learning_ (section 4.5). Berlin, Heidelberg: Springer-Verlag.
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