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https://issues.apache.org/jira/browse/MADLIB-1181?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Frank McQuillan updated MADLIB-1181:
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Description:
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 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
regression score has to be computed (avg or weighted avg).
This JIRA applies to regression only not classification, because classification
uses majority voting.
was:
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).
> 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: v1.14
>
>
> 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 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
> regression score has to be computed (avg or weighted avg).
> This JIRA applies to regression only not classification, because
> classification uses majority voting.
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