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From "Stavros Kontopoulos (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (FLINK-5525) Streaming Version of a Linear Regression model
Date Sat, 21 Jan 2017 17:38:26 GMT

    [ https://issues.apache.org/jira/browse/FLINK-5525?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15833070#comment-15833070
] 

Stavros Kontopoulos edited comment on FLINK-5525 at 1/21/17 5:38 PM:
---------------------------------------------------------------------

[~mtunqiue] Sure I agree there are other algorithms eg. clustering which may have a streaming
version feel free to open others and work on them. If you want to co-ordinate on this let
me know.
For example we need to set the abstractions. Check Spark implementation for an example of
what the abstractions might be. I didn't open other issues because I wanted to see what people
think first. 


was (Author: skonto):
[~mtunqiue] Sure I agree there other algorithms eg. clustering which may have a streaming
version feel free to open others and work on them. If you want to co-ordinate on this let
me know.
For example we need to set the abstractions. Check Spark implementation for an example of
what the abstractions might be. I didn't open other issues because I wanted to see what people
think first. 

> Streaming Version of a Linear Regression model
> ----------------------------------------------
>
>                 Key: FLINK-5525
>                 URL: https://issues.apache.org/jira/browse/FLINK-5525
>             Project: Flink
>          Issue Type: New Feature
>          Components: Machine Learning Library
>            Reporter: Stavros Kontopoulos
>
> Given the nature of Flink we should have a streaming version of the algorithms when possible.
> Update of the model should be done on a per window basis.
> An extreme case is: https://en.wikipedia.org/wiki/Online_machine_learning
> Resources
> [1] http://scikit-learn.org/dev/modules/scaling_strategies.html#incremental-learning
> [2] http://stats.stackexchange.com/questions/6920/efficient-online-linear-regression
> [3] https://spark.apache.org/docs/1.1.0/mllib-linear-methods.html



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