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From "Joseph K. Bradley (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-4980) Add decay factors to streaming linear methods
Date Mon, 03 Aug 2015 20:01:04 GMT

     [ https://issues.apache.org/jira/browse/SPARK-4980?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Joseph K. Bradley updated SPARK-4980:
-------------------------------------
    Target Version/s: 1.6.0  (was: 1.5.0)

> Add decay factors to streaming linear methods
> ---------------------------------------------
>
>                 Key: SPARK-4980
>                 URL: https://issues.apache.org/jira/browse/SPARK-4980
>             Project: Spark
>          Issue Type: New Feature
>          Components: MLlib, Streaming
>            Reporter: Jeremy Freeman
>            Priority: Minor
>
> Our implementation of streaming k-means uses an decay factor that allows users to control
how quickly the model adjusts to new data: whether it treats all data equally, or only bases
its estimate on the most recent batch. It is intuitively parameterized, and can be specified
in units of either batches or points. We should add a similar decay factor to the streaming
linear methods using SGD, including streaming linear regression (currently implemented) and
streaming logistic regression (in development).



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