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From "Mikio Braun (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (FLINK-1723) Add cross validation for parameter selection and validation
Date Fri, 22 May 2015 13:57:17 GMT

     [ https://issues.apache.org/jira/browse/FLINK-1723?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Mikio Braun reassigned FLINK-1723:
----------------------------------

    Assignee: Mikio Braun

> Add cross validation for parameter selection and validation
> -----------------------------------------------------------
>
>                 Key: FLINK-1723
>                 URL: https://issues.apache.org/jira/browse/FLINK-1723
>             Project: Flink
>          Issue Type: New Feature
>          Components: Machine Learning Library
>            Reporter: Till Rohrmann
>            Assignee: Mikio Braun
>              Labels: ML
>
> Cross validation [1] is a standard tool to select proper parameters for you model and
to validate your results. As such it is a crucial tool for every machine learning library.
> The cross validation should work with arbitrary learners and ranges of parameters you
can specify. A first cross validation strategy it should support is the k-fold cross validation.
> Resources:
> [1] [http://en.wikipedia.org/wiki/Cross-validation]



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