[jira] [Closed] (MADLIB-1181) Add an option for weighted average in k-NN

2018-02-14 Thread Frank McQuillan (JIRA)

 [ 
https://issues.apache.org/jira/browse/MADLIB-1181?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Frank McQuillan closed MADLIB-1181.
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> Add an option for weighted average in k-NN
> --
>
> Key: MADLIB-1181
> URL: https://issues.apache.org/jira/browse/MADLIB-1181
> Project: Apache MADlib
>  Issue Type: Improvement
>  Components: k-NN
>Reporter: Frank McQuillan
>Assignee: Himanshu Pandey
>Priority: Minor
> Fix For: v1.14
>
>
> Follow on from 
> https://issues.apache.org/jira/browse/MADLIB-1059
> (please see this JIRA for additional comments)
> MADlib does a simple average of the k-nearest neighbors to come up with the
> final value for classification and regression. Doing a weighted average 
> instead
> might be a desirable functionality. The weighting for the average can be 
> based on the
> distance of the k-nearest neighbors.
> We can probably provide an optional parameter to let users choose how the 
> final
> score has to be computed (avg or weighted avg).
> This JIRA applies to classification and regression.



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[jira] [Closed] (MADLIB-1181) Add an option for weighted average in k-NN voting.

2017-12-13 Thread Nikhil (JIRA)

 [ 
https://issues.apache.org/jira/browse/MADLIB-1181?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Nikhil closed MADLIB-1181.
--
Resolution: Fixed

> Add an option for weighted average in k-NN voting.
> --
>
> Key: MADLIB-1181
> URL: https://issues.apache.org/jira/browse/MADLIB-1181
> Project: Apache MADlib
>  Issue Type: Improvement
>  Components: k-NN
>Reporter: Frank McQuillan
>Assignee: Himanshu Pandey
>Priority: Minor
> Fix For: v1.13
>
>
> Follow on from 
> https://issues.apache.org/jira/browse/MADLIB-1059
> (please see this JIRA for additional comments)
> MADlib does a simple average of the k-nearest neighbors to come up with the
> final value for both classification and regression. Doing a weighted average 
> instead
> might be a desirable functionality. The weighting for the average can be 
> based on the
> distance of the k-nearest neighbors.
> We can probably provide an optional parameter to let users choose how the 
> final
> classification label or regression score has to be computed (avg or weighted 
> avg).



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