Pat Ferrel created MAHOUT-1020:
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             Summary: The Cluster Evaluator is returning bad results
                 Key: MAHOUT-1020
                 URL: https://issues.apache.org/jira/browse/MAHOUT-1020
             Project: Mahout
          Issue Type: Bug
          Components: Clustering
    Affects Versions: 0.6
         Environment: Various environments and data sets. Mahout 0.6, 0.7 trunk 
not tested.
            Reporter: Pat Ferrel
             Fix For: 0.7


Conversation with between Pat Ferrel and Jeff Eastman on the user list

Hi Pat,

I don't have a good answer here. Evidently, something in CDbw has become broken 
and you are the first to notice. When I run TestCDbwEvaluator, the values for 
k-means and fuzzy-k are clearly incorrect. The values for Canopy, MeanShift and 
Dirichlet are not so obviously incorrect but I remain suspicious. Something 
must have become broken in the recent clustering refactoring.

>From the method CDbwEvaluator.invalidCluster comment (used to enable pruning):
   * Return if the cluster is valid. Valid clusters must have more than 2 
representative points,
   * and at least one of them must be different than the cluster center. This 
is because the
   * representative points extraction will duplicate the cluster center if it 
is empty.

Oddly enough, inspection of the test log indicates that only k-means and 
fuzzy-k are not pruning clusters. Clearly some more investigation is needed. I 
will take a look at it tomorrow. In the mean time if you develop any additional 
insight please do share it with us.

Thanks,
Jeff

On 5/17/12 3:53 PM, Pat Ferrel wrote:
> I built a tool that iterates through a list of values for k on the same data 
> and spits out the CDbw and ClusterEvaluator results each time.
>
> When the evaluator or CDbw prunes a cluster, how do I interpret that? They 
> seem to throw out the same clusters on a given run. Also CDbw always returns 
> an inter-cluster density of 0?


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