Re: [Databionic-ESOM-User] iris data set

[Davide C. <daw...@gm...>]

On Oct 12, 2007, at 9:40 PM, Niko Efthymiou wrote:

> On Friday 12 October 2007, davide cittaro wrote:
>> Hi again,I was trying to better understand how ESOM tools work and
>> perform. I tried with a well-known data set: Iris classification. I
>> used the one provided in Weka, converted in iris.lrn+iris.cls.
>> I tried a standard esom training run, with a 64x64 map, 30 epochs, 31
>> starting radius and default values for all the rest...
>
> 64x64 is way too large for the iris data set. The set is only 55  
> samples
> vs. 4096 neurons...
>
> 24x24 or 16x32 are a starting point. Also don't forget to  
> preprocess the
> data. ZT and Robust-ZT which are builtin the esom tools are a start,
> but there might be more sopfisticated transformations.
>

Oh great! Thank you! Is there some recommendation about neurons/ 
samples ratio?
>
>> Hi again, and sorry for bothering one more time.I've been reading
>> "Emergence in Self Organizing Feature Maps" (Ultsch A.) and I figured
>> out that I may need U*C clustering tools to complete analysis of my
>> data.
>
> AFAIK, it hasn't been implemented in ESOM-tools. Maybe its in the  
> matlab
> stuff, but I don't realy know.

D'oh!
Thank you for the hints and the answers so far.



dawe

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