######## I am sending it again with the correct Subject line, I am sorry 
about that ########

Hello,

I am using Sklearn in combination with Pytables for Automated Genre 
Identification of Web Pages.

The reason I am using Pytables is for executing Very hight Scale 
Evaluation of SVM using 50,000 samples for training. I know that that 
might probably this will not have so much impact in my results. However, 
due to the extreme chaotic nature of the textual information on the WEB, 
I would like to assure that the Scale will have not Impact on learning 
or vice versa.

So, is there a any tip for me to fit() the model in stages i.e not to 
bring the whole data set in Memory during the learning process. As I can 
see in my code when I am giving an EArray as an argument to Fit() it 
seem to load everything in memory in order to train the model, so I 
cannot exploit the Pytables feature i.e Arrays to "Live" on the Disk and 
not on the Ram.

Any Enlightenment tips for me?

Thank you very much.

Best Regards,

Dimitrios

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