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https://issues.apache.org/jira/browse/MAHOUT-54?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12595941#action_12595941
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Jeff Eastman commented on MAHOUT-54:
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I downloaded this patch and it installed cleanly, but I have several concerns
about it:
- the patch introduces an entirely new canopykmeans package without much
motivation. In particular, it is not clear what improvements it is suggesting
for either canopy or kmeans
- there are no unit tests included that would indicate that the code produces
correct results
- the pretty-printing rules are not those specified by ASF: the Java
conventions with tabs replaced by 2 spaces vs. 4 spaces. The patch changes
several of the existing canopy files formatting unnecessarily
- the patch introduces @author tags which are not according to ASF policy.
These were likely added by Eclipse but should be removed
I would prefer to understand the logic changes which are being suggested first,
then see a minimal patch to introduce such changes. This patch introduces an
entirely new implementation that is derived from the original version, but
cannot be easily compared with it. And, it has no associated tests.
I'm interested in understanding if logic improvements to either canopy or
kmeans can be made, but from this patch it is too difficult to understand what
is being proposed. Could you please try to be a little more systematic?
> parallelize k-means sharing the predominance of canopies
> --------------------------------------------------------
>
> Key: MAHOUT-54
> URL: https://issues.apache.org/jira/browse/MAHOUT-54
> Project: Mahout
> Issue Type: Improvement
> Components: Clustering
> Affects Versions: 0.1
> Environment: OS Independent
> Reporter: Jeremy Chow
> Fix For: 0.1
>
> Attachments: canopykeams.patch
>
>
> The implementation of mahout at present only using canopy algorithm creating
> initial cluster centroids for k-means. It will calculate the distance from
> each center to every point while iterating. But the most import improvement
> of canopies is that needs only calculating the distance from each center to
> a much smaller number of points which exists in the same canopy.
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