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Posted to issues@spark.apache.org by "Jeremy Freeman (JIRA)" <ji...@apache.org> on 2014/12/28 22:32:13 UTC

[jira] [Created] (SPARK-4980) Add decay factors to streaming linear methods

Jeremy Freeman created SPARK-4980:
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             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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