[BioC] PhD student need advice

[Steve Lianoglou]

Hi,

(1) Clippy says:

"It looks like your working on a collaborative filtering project"

(or something that can be reduced to it)

In which case you can start your "hunt" (reading up on the field, etc.) here:
http://www.grouplens.org/projects


(2) This is the wrong forum for this question as your question (as
currently phrased, at least) has little to do with bioinformatics, and
even less so with bioconductor.

Perhaps an appropriate place to ask questions of what appears to fall
in the realm of a machine learning problem would be metaoptimize:

http://metaoptimize.com/qa/

But I suggest you do a bit more homework before you post there .. as
well as ask a more specific question -- what is your end goal? You say
that "k-means" may not be suitable for this case, so I guess you have
an idea of what a suitable outcome is  -- be more specific about what
that might be, ie. how will you know when the end result of whatever
black box you stuff your data through (whether it be kmeans or
whatever) is a good result?

Good luck!
-steve




On Thu, Aug 2, 2012 at 11:27 AM, Al-Mamovy, Huda
<N.N.Al-Mamovy at ljmu.ac.uk> wrote:
> Dear sir,
> I have dataset of users , I found the similarity among them ,then got similarity network
> say
> 100*100
> Now, i have to make clustering of users depending on their similarties .
> but I do not know , from where I have to begin.
> is k-mean suitable for this case?
> or newman or ward algorithm .
> I do appreciate your help
> with my best regards,, huda
>
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-- 
Steve Lianoglou
Graduate Student: Computational Systems Biology
 | Memorial Sloan-Kettering Cancer Center
 | Weill Medical College of Cornell University
Contact Info: http://cbio.mskcc.org/~lianos/contact