Re: [Fwd: Re: [Databionic-ESOM-User] ESOM]

[<fa...@Ma...>]

Hi Katerina,

the format of your file looks ok. the data itself looks quite weird. there
are only few unique values in most columns with many duplicates. this
seems to throw off the pareto density estimatio course into an endless
loop finally running out of memory. the actual training suceeds, only the
subsequent centering of the map around the closest neuron is affected. you
can work around this using the command line option "-dc" (= don't center),
that is, unfortunately only available on the command line, not in the gui.

since our ressources are currently very limited I don't know when this can
be fixed. It does seem like a very unlikely case caused by your actual
dataset to me.

I strongly recommend you to look closer at your data before you feed into
ESOM or any clustering algorithm, in particular the scales of the
variables that differ tremendously in your file.

bye
fabian

> Dear Fabian,
> I am facing some problems using eSOM and your help would be very valuable
> for me.
> I am using eSOM for an .lrn file and when I try to perform training (with
> the default parameters) I receive the following message
>
> spheres for 18-tile contain on average 65% of the data searching pareto
> radius ...
>
>
> and finally
>
> at databionics.math.ParetoDensity.getParetoRadius(ParetoDensity.java:156)
> at databionics.math.ParetoDensity.getParetoRadius(ParetoDensity.java:323)
>
> The training can not be completed it stops in 95%.
>
> I don't understand what is wrong??
>  I suppose that something is wrong with the lrn file used for the
> training.
> I attach the file used for the training.
>
> I would appreciate it if you could help me.
>
> Thanking you in advance.
> Katerina
>
>
>>> @fabian could you please set the reply-to headers for the list?
>>
>> done
>>
>>> Katerina Mitrokotsa wrote:
>>>
>>>>I have recently tried to use ESOm and although I have found it really
>>>> interesting I can't understand if there is a way to inspect neuron
>>>> values Does this tool permit us to see which samples of data
>>>> correspond to which neuron?
>>>
>>>
>>> You can select the samples in the Data tab at the bottom, which are
>>> then highlighted.
>>
>> addition: you can also select neurons in the map with the data mouse
>> (activate the leftmost icon in the toolbar). the data points assigned to
>> these neurons will be displayed in the data tab at the bottom. you can
>> also load a *.names file with text labels for the data points. these
>> will be displayed in the last columns of the data table.
>>
>>>>Furthermore which is the procedure in order to use a dataset for
>>>> training and then another dataset for testing.
>>>
>>> To do this you have to add classmasks to your ESOM and then use the
>>> Project tool to see if the test set is projected into the correct
>>> classes. The prosses isn't automated as far as i know (fabian?)
>>
>> creating the class masks is manual (in cvs there is some semi-automated
>> support with flood filling already). projection is automated and can be
>> run via the menu or the command line. short summary:
>>
>> - create two seperate *.lrn for training and test data
>> - train ESOM with training data
>> - optional: load *.cls with known classification of training data
>> - identify clusters and create class mask (also *.cls)
>> - load *.lrn with test data
>> - project this data on ESOM
>> - save newly created *.cls for test data
>> - optional: analyze *.cls for test data, e.g. compare to *.cls with
>> known classification of test data.
>>
>> we offer no tools for the last step which is rather easy however. i
>> could post some matlab code, if you wish.
>>
>> bye
>> fabian
>>
>>
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