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https://issues.apache.org/jira/browse/MAHOUT-524?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13142530#comment-13142530
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Grant Ingersoll commented on MAHOUT-524:
----------------------------------------
Making this change does indeed get us well past that problem and leads to:
{quote}
Exception in thread "main" java.lang.NullPointerException
at org.apache.mahout.math.DenseVector.assign(DenseVector.java:133)
at
org.apache.mahout.math.decomposer.lanczos.LanczosSolver.solve(LanczosSolver.java:160)
at
org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver.runJob(DistributedLanczosSolver.java:72)
at
org.apache.mahout.clustering.spectral.kmeans.SpectralKMeansDriver.run(SpectralKMeansDriver.java:155)
at
org.apache.mahout.clustering.display.DisplaySpectralKMeans.main(DisplaySpectralKMeans.java:72)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
at java.lang.reflect.Method.invoke(Method.java:597)
at com.intellij.rt.execution.application.AppMain.main(AppMain.java:120)
{quote}
Not sure if that is a direct correlation to my change or not, but continue to
debug
> 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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