[jira] [Assigned] (SPARK-5362) Gradient and Optimizer to support generic output (instead of label) and data batches

["Apache Spark (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-5362?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-5362:
-----------------------------------

    Assignee: Apache Spark

> 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
>            Assignee: Apache Spark
>   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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