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From "Jeremy Freeman (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SPARK-4980) Add decay factors to streaming linear methods
Date Sun, 28 Dec 2014 21:32:13 GMT
Jeremy Freeman created SPARK-4980:
-------------------------------------

             Summary: 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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