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From Pat Ferrel <...@occamsmachete.com>
Subject CDbw and Evaluator results
Date Tue, 22 May 2012 18:02:29 GMT
I'm using mahout 0.6 and so may not be seeing the same results as you.

I take it that the inter-cluster distance of 0 is a bug and pruning 
should not happen very often?

I haven't used this before so I'm not sure if my CDbw or Evaluator 
results are wrong in other ways.

Should I create a bug for this in Jira?

On 5/17/12 2:33 PM, Jeff Eastman 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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