Re: [Databionic-esom-user] Parameter Selection for ESOM

[Michael D. J. <mic...@ya...>]

Hi Mario,
 
 
Thank you for the valuable information you have provided. 
 
 
Michael
 


Mario Noecker <noe...@Ma...> wrote:Hi Michael,

there are no real researchs on gridsize, but I can tell you, what I
prefere. By using a dataset with 5000 instances, I would use a grid with
about 90 rows and 125 columns. if you have 5000 instances then you need
at least 10000 neurons.

In any event the neighborhood radius is a question of the kind of
neighbohoodfunction you are using. Mostly I use the gaussian
neighborhood. By gaussian neighborhood a good starting value is half of
the smaller dimension of the grid. In a training with our 90*125 grid,
this will be about 45. More then this isn`t really usefull, because some
neurons get changed more then one time during the update of one neuron.
(if you are using the toroid grid, what we are recommending) But in the
first epoch it is usefull to change nearly the whole map in one update.
If you are using the bubble neighborhoodfunction probably it is
senseless to update the whole map, because every neuron will be changed
the same way.

A training with such a big dataset, grid and radius will take a really
long time. Maybe you can use the batch version, which gives a speed up
of 25%.

sent your next message to the whole list, maybe some other guys want to
replie something.

bye
mario


> Dear Mario,
> 
> Thank you very much for your VERY QUICK response. It is very much
> appreciated.
> 
> I am glad that you mention that the size of the grid depends on the
> size of the dataset. I am aware that we need much more neurons than
> datapoints. However, is there an *approximate* rule for this? (E.g. If
> you have a dataset made up of 5000 instances, what would be a range
> for the size of the grid?)From your experience, what is the size of
> the dataset you use when the size of the grid is 50 by 82 and 70 by 110?
> 
> 
> In addition, in terms of the size of the neighbourhood, what is a good
> approximate rule to follow? Moreover, in a grid where there are much
> more neurons than datapoints (e.g. a 100 to 1 ratio), what would the
> impact of a bigger or smaller neighborhood be?
> 
> I would like to thank you in advance for your continued support.
> Regards,
> Michael
> 
>
> */Mario Noecker /* wrote:
>
> Hi Michael,
>
> the best size of the grid depends on the size of the dataset. Using
> emergent SOMs you need of course much more neurons then datapoints.
> Mostly we use grids with 50 rows and 82 columns, or 70 rows and 110
> columns. We realized grids with a rectangular shape offer the best
> results.
>
> We mostly use 20-30 epochs of training without relating to the
> gridsize.
>
> if there are more questions, please ask.
>
> mario
>
> Michael Dell Junior wrote:
>
> > Hi all,
> >
> > Congratulations on the development effort for the production of
> such a
> > good tool.
> >
> > I have a few questions regarding the use of the tool:
> >
> >
> > 1) Is there a "right number" for the size of the grid for
> convergence
> > to occur?
> > 2) Is there a relationship (or a rule of thumb) between the
> number of
> > traning instances used and the right size of the grid?
> >
> >
> >
> > Your help will be very much appreciated.
> >
> > Regards,
> > Michael Dell Junior
> >
> >
> >
> >
> ------------------------------------------------------------------------
> > Post your free ad now! *Yahoo! Canada Personals*
> >
>
>
>
> ------------------------------------------------------------------------
> Post your free ad now! *Yahoo! Canada Personals*
> 






---------------------------------
Post your free ad now! Yahoo! Canada Personals