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https://issues.apache.org/jira/browse/MAHOUT-24?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12666101#action_12666101
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Alexander Hans commented on MAHOUT-24:
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> Alexander did you further pursue this issue?
Sorry for being so quiet on this one, the last couple of months have been
somewhat stressful for me day job-wise, so I didn't find any time to work on
this issue. I think things will become easier in a few weeks.
Ted, thanks for pointing out other methods for inverting a matrix. For a single
LWLR prediction this has to be done only once by the reducer, so I think it
would be ok to implement whatever method works for a first version and change
it later to something better once the whole algorithm is functional.
> Skeletal LWLR implementation
> ----------------------------
>
> Key: MAHOUT-24
> URL: https://issues.apache.org/jira/browse/MAHOUT-24
> Project: Mahout
> Issue Type: New Feature
> Environment: n/a
> Reporter: Samee Zahur
> Attachments: LWLR.patch.tar.bz2
>
>
> This is a very skeletal but functional implementation for LWLR. It outputs n
> lines where n is the number of dimensions. ith line = sum(x[i]*x[ind]) where
> ind is the index of independant variable. So the actual gradient = 2nd
> line/1st line for the classical 2D.
> Contains a single small test case for demonstration.
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