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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-5362) Gradient and Optimizer to support generic output (instead of label) and data batches
Date Thu, 22 Jan 2015 01:03:58 GMT

    [ https://issues.apache.org/jira/browse/SPARK-5362?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14286701#comment-14286701
] 

Apache Spark commented on SPARK-5362:
-------------------------------------

User 'avulanov' has created a pull request for this issue:
https://github.com/apache/spark/pull/4152

> Gradient and Optimizer to support generic output (instead of label) and data batches
> ------------------------------------------------------------------------------------
>
>                 Key: SPARK-5362
>                 URL: https://issues.apache.org/jira/browse/SPARK-5362
>             Project: Spark
>          Issue Type: Improvement
>          Components: MLlib
>    Affects Versions: 1.2.0
>            Reporter: Alexander Ulanov
>             Fix For: 1.3.0
>
>   Original Estimate: 24h
>  Remaining Estimate: 24h
>
> Currently, Gradient and Optimizer interfaces support data in form of RDD[Double, Vector]
which refers to label and features. This limits its application to classification problems.
For example, artificial neural network demands Vector as output (instead of label: Double).
Moreover, current interface does not support data batches. I propose to replace label: Double
with output: Vector. It enables passing generic output instead of label and also passing data
and output batches stored in corresponding vectors.



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