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https://issues.apache.org/jira/browse/MAHOUT-1030?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13679620#comment-13679620
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Pat Ferrel commented on MAHOUT-1030:
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Not really. What I do now is recalculate the distance to the centroid when I
store the vectors in a DB.
What used to happen, pre 0.8 (or ?) was the distance was stored in a
WeightedPropertyVectorWritable, in the properties. During the kmeans
refactoring of 0.8 the type of the vector was changed to NamedVectorWritable so
the property that held the distance was lost. To put back
WeightedPropertyVectorWritable and store the distance in it was more than I
wanted to maintain outside of the trunk.
So I just recalculate it.
> Regression: Clustered Points Should be WeightedPropertyVectorWritable not
> WeightedVectorWritable
> ------------------------------------------------------------------------------------------------
>
> Key: MAHOUT-1030
> URL: https://issues.apache.org/jira/browse/MAHOUT-1030
> Project: Mahout
> Issue Type: Bug
> Components: Clustering, Integration
> Affects Versions: 0.7
> Reporter: Jeff Eastman
> Assignee: Suneel Marthi
> Fix For: 0.8
>
> Attachments: MAHOUT-1030.patch, MAHOUT-1030.patch, MAHOUT-1030.patch
>
>
> Looks like this won't make it into this build. Pretty widespread impact on
> code and tests and I don't know which properties were implemented in the old
> version. I will create a JIRA and post my interim results.
> On 6/8/12 12:21 PM, Jeff Eastman wrote:
> > That's a reversion that evidently got in when the new
> > ClusterClassificationDriver was introduced. It should be a pretty easy fix
> > and I will see if I can make the change before Paritosh cuts the release
> > bits tonight.
> >
> > On 6/7/12 1:00 PM, Pat Ferrel wrote:
> >> It appears that in kmeans the clusteredPoints are now written as
> >> WeightedVectorWritable where in mahout 0.6 they were
> >> WeightedPropertyVectorWritable? This means that the distance from the
> >> centroid is no longer stored here? Why? I hope I'm wrong because that is
> >> not a welcome change. How is one to order clustered docs by distance from
> >> cluster centroid?
> >>
> >> I'm sure I could calculate the distance but that would mean looking up the
> >> centroid for the cluster id given in the above WeightedVectorWritable,
> >> which means iterating through all the clusters for each clustered doc. In
> >> my case the number of clusters could be fairly large.
> >>
> >> Am I missing something?
> >>
> >>
> >
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