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https://issues.apache.org/jira/browse/MAHOUT-524?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13108486#comment-13108486
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Hudson commented on MAHOUT-524:
-------------------------------

Integrated in Mahout-Quality #1051 (See 
[https://builds.apache.org/job/Mahout-Quality/1051/])
    MAHOUT-524 added danbri's setJarByClass() patch and logging

srowen : http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1172995
Files : 
* 
/mahout/trunk/core/src/main/java/org/apache/mahout/clustering/spectral/common/AffinityMatrixInputJob.java
* 
/mahout/trunk/core/src/main/java/org/apache/mahout/clustering/spectral/common/AffinityMatrixInputMapper.java
* 
/mahout/trunk/core/src/main/java/org/apache/mahout/clustering/spectral/common/MatrixDiagonalizeJob.java
* 
/mahout/trunk/core/src/main/java/org/apache/mahout/clustering/spectral/common/UnitVectorizerJob.java
* 
/mahout/trunk/core/src/main/java/org/apache/mahout/clustering/spectral/common/VectorCache.java
* 
/mahout/trunk/core/src/main/java/org/apache/mahout/clustering/spectral/common/VectorMatrixMultiplicationJob.java


> DisplaySpectralKMeans example fails
> -----------------------------------
>
>                 Key: MAHOUT-524
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-524
>             Project: Mahout
>          Issue Type: Bug
>          Components: Clustering
>    Affects Versions: 0.4, 0.5
>            Reporter: Jeff Eastman
>            Assignee: Shannon Quinn
>              Labels: clustering, k-means, visualization
>             Fix For: 0.6
>
>         Attachments: EclipseLog_20110918.txt, 
> SpectralKMeans_fail_20110919.txt, aff.txt, raw.txt, spectralkmeans.png
>
>
> I've committed a new display example that attempts to push the standard 
> mixture of models data set through spectral k-means. After some tweaking of 
> configuration arguments and a bug fix in EigenCleanupJob it runs spectral 
> k-means to completion. The display example is expecting 2-d clustered points 
> and the example is producing 5-d points. Additional I/O work is needed before 
> this will play with the rest of the clustering algorithms. 

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