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

From: Milan Rusev (milan.rusev_at_[hidden])
Date: 2008-03-25 04:16:48

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.