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lib/AI/NeuralNet/SOM.pm  view on Meta::CPAN

               [ -1, -1, -1 ], 
               [ 0, 4, -3]);

=cut

sub train {
    my $self   = shift;
    my $epochs = shift || 1;
    die "no data to learn" unless @_;

    $self->{LAMBDA} = $epochs / log ($self->{_Sigma0});                                 # educated guess?

    my @mes    = ();                                                                    # this will contain the errors during the epochs
    for my $epoch (1..$epochs)  {
	$self->{T} = $epoch;
	my $sigma = $self->{_Sigma0} * exp ( - $self->{T} / $self->{LAMBDA} );          # compute current radius
	my $l     = $self->{_L0}     * exp ( - $self->{T} / $epochs );                  # current learning rate

	my @veggies = @_;                                                               # make a local copy, that will be destroyed in the loop
	while (@veggies) {
	    my $sample = splice @veggies, int (rand (scalar @veggies) ), 1;             # find (and take out)