Thanks for the fast reply Uwe.

My hope in posting this was to find if anyone had already done work (in R)
in this direction.  So far I wasn't able to find any such relevant code, so
I turned to the mailing list.

Regarding new implementations - thanks for offering! - I have already came
around one such algorithm - I implemented it, and will probably publish it
on my blog <http://www.r-statistics.com/> in the near future.

If any one else has any reference to R implementation, it would be most
helpful,
Tal


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2010/4/21 Uwe Ligges <lig...@statistik.tu-dortmund.de>

> On 21.04.2010 18:15, Tal Galili wrote:
>
>> Hello all,
>>
>> I would like to compare the similarity of two cluster solutions using a
>> validation criteria (such as Hubert's gamma coefficient, the Dunn index
>> the
>> corrected rand index and so on)
>>
>> I see (from here:http://www.statmethods.net/advstats/cluster.html) that
>> the function cluster.stats() in the fpc package provides a mechanism
>> for comparing 2 cluster solutions - *BUT* - it requires me to give the
>> the distance matrix among objects.
>>
>> *My question *is: What ways can you suggest for comparing two cluster
>> solutions, while using the cluster indicators only (i.e: a vector saying
>> to
>> which cluster each object belongs to), and WITHOUT asking to submit the
>> distance matrix between the objects.
>>
>
> Don't know. If you have a theoretical solution and can provide the
> description of a method, there will be many people around happy to make an
> algorithm and implement it.
>
> Uwe Ligges
>
>
>
>  Thanks,
>> Tal
>>
>>
>>
>> ----------------Contact
>> Details:-------------------------------------------------------
>> Contact me: tal.gal...@gmail.com |  972-52-7275845
>> Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) |
>> www.r-statistics.com (English)
>>
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>>
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>>
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