I am not asking about k-means. I am asking about passing initial
assignments to the kernel k means algorithm. In kernel k-means, centroids
are not defined explicitly. I tried passing initial centroids in the
original feature space though. But, it did not work. The provided example
just sets the number of clusters and lets the method assigns random cluster
memberships. I am also wondering about the output centers. Are they the
centers in the eigenvectors space? If so, what kind of initial centers I am
supposed to pass to the method?

--ahmed

On Wed, Apr 3, 2013 at 12:54 AM, Pascal Oettli <kridox@ymail.com> wrote:

> Hi,
>
> I would say that if you know what k-means algorithm is, you know the
> meaning of "initial cluster centers".
>
> You can also check the output of the provided example.
>
> Regards,
> Pascal
>
>
> On 04/03/2013 09:27 AM, Ahmed Elgohary wrote:
>
>> Hi,
>>
>> I am trying to pass initial cluster assignments to the kkmeans
>> method<http://rss.acs.unt.edu/**Rdoc/library/kernlab/html/**kkmeans.html<http://rss.acs.unt.edu/Rdoc/library/kernlab/html/kkmeans.html>
>> >of
>>
>> kernlab. It is not clear to me how I can set the parameter
>> *centers* with "initial cluster centers" as stated in the documentation?
>>
>> thanks,
>>
>> --ahmed
>>
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>>
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>>
>>

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