Re: Request for Comments: New IPv6 OS detection machine learning engine

[Varunram Ganesh <vrg2009 () ymail com>]

>      5) As we already thought, having 695 features is quite a lot.
>      Approaches to reduce the amount of features could be for example
>
>      using neural networks or principal component analysis (PCA). We
>      did play around with such things a bit before, but it might be
>      interesting
>
>      to have another look.
>
>
> I'm not exactly familiar with these either, but it definitely sounds
> like it's worth a look!

> Unfortunately, me neither. Anyone who is is welcome to apply to the next
> Google Summer of Code!

I think PCA might be a better choice considering we have a dataset of slightly greater than 300 fingerprints and for 
neural networks to work correctly, we would need as many fingerprints as features. That being said, as you mentioned, 
it'd be helpful to have more fingerprints to make the algorithm better (and maybe implement neural networks in the 
future).
Cheers,Varunram 

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