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From Pat Ferrel <...@occamsmachete.com>
Subject Re: Judging the quality of clustering
Date Thu, 17 May 2012 23:07:23 GMT
I'm only on 0.6, nothing very recent.

Sent from my iPhone

On May 17, 2012, at 2:33 PM, Jeff Eastman <jdog@windwardsolutions.com> wrote:

> 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?
>> 
>> On 5/17/12 5:58 AM, Jeff Eastman wrote:
>>> Yes, that is the paper I used to implement CDbw. I've tried it a few times along
with the simpler ClusterEvaluator metrics I took from Mahout In Action and they look to be
reasonable - see the tests - though I have no way to judge their absolute values. Anything
you can contribute in this area would be most welcome. Perhaps a wiki page?
>>> 
>>> 
>>> On 5/16/12 1:14 PM, Pat Ferrel wrote:
>>>> The reference was in the code for http://www.db-net.aueb.gr/index.php/corporate/content/download/227/833/file/HV_poster2002.pdf
>>>> 
>>>> On 5/16/12 9:56 AM, Pat Ferrel wrote:
>>>>> Thanks, I've been looking at that. Is there a description of how to interpret
those values? An academic paper maybe? The intra-cluster distance intuitively seems to correspond
to something like cohesion. I don't get the intuition behind inter-cluster distances but Ted
thinks they are the most important.
>>>>> 
>>>>> On 5/16/12 7:32 AM, Jeff Eastman wrote:
>>>>>> Mahout has a ClusterEvaluator and a CDbwEvaluator that compute some
quality metrics (inter-cluster distance, intra-cluster-distance, ...) that you may find useful.
Both calculate a set of representative points from the clustering output and compute the (n^2)
metrics over these points rather than all of the points in each cluster.
>>>>>> 
>>>>>> On 5/15/12 4:46 PM, Pat Ferrel wrote:
>>>>>>> So many questions about best k, how to choose t1 and t2, how
much help is dimensional reduction would have clear answers if we had a way to judge the quality
of clusters.
>>>>>>> 
>>>>>>> Various methods were discussed here for a time: http://www.lucidimagination.com/search/document/dab8c1f3c3addcfe/validating_clustering_output
>>>>>>> 
>>>>>>> Has there been any work on building a measure of quality?
>>>>>>> 
>>>>>>> 
>>>>>> 
>>>> 
>>>> 
>>> 
>> 
>> 
> 

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