Re: [boost] [gsoc 2008] Neural Networks library

From: Barco You (barcojie_at_[hidden])
Date: 2008-03-25 05:17:19

Looks good, I like distribution world.
But as you described, there is only distribution, what about the algorithms
such as Bayes, Maximum Likelihood ...
and they are not restricted to specific distributions.

On Tue, Mar 25, 2008 at 4:16 PM, Milan Rusev <milan.rusev_at_[hidden]> wrote:

> OK, a statistics library sounds better to me, too.
>
> So how about that (speaking in pseudo code):
>
>
>
> There is a base class:
>
> distribution
>
> {
>
> get_probability(value); // P(value)
>
> get_comulutative_probability(value); //P(x <= value)
>
> generate_random();
>
> get_expectation();
>
> get_variance();
>
> //more
>
> }
>
>
>
> Specific distributions will derive from it and expose their parameters
> too;
>
> discrete distributions may have a method get_values().
>
>
>
> Factories:
>
> distribution create_distribution(samples, distribution_type); // given a
> specific distribution and
>
> a set of samples find the MLE (the parameters of the distribution);
> implemented specifically for each distribution
>
>
>
> distribution create_ distribution(samples); // given a set of samples
> approximate an
>
> unknown distribution (e.g. with a Monte Carlo or smth like this);
>
> maybe the method for the generation will be a parameter too.
>
>
>
> There may be methods of inferring some properties of a distribution
> without
> generating the whole of it first.
>
>
>
> Operations:
>
> distribution create_joint_distr(distribution, distribution);
>
> distribution create_sum(distribution, distribution);
>
> distribution create_difference(distribution, distribution);
>
>
>
> Other things I can think of.
>
>
>
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-- 
-------------------------------
Enjoy life!
Barco You