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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