AI-NeuralNet-Kohonen

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

An epoch is composed of A number of generations, the number being
the total number of input vectors.

For every generation, iterates:

=over 4

=item 1

selects a target from the input array (see L</PRIVATE METHOD _select_target>);

=item 2

finds the best-matching unit (see L</METHOD find_bmu>);

=item 3

adjusts the neighbours of the BMU (see L</PRIVATE METHOD _adjust_neighbours_of>);

=back

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

=cut

sub train { my ($self,$epochs) = (shift,shift);
	$epochs = $self->{epochs} unless defined $epochs;
	&{$self->{train_start}} if exists $self->{train_start};
	for my $epoch (1..$epochs){
		$self->{t} = $epoch;
		&{$self->{epoch_start}} if exists $self->{epoch_start};
		for (0..$#{$self->{input}}){
			my $target = $self->_select_target;
			my $bmu = $self->find_bmu($target);
			$self->_adjust_neighbours_of($bmu,$target);
		}
		$self->_decay_learning_rate;
		&{$self->{epoch_end}} if exists $self->{epoch_end};
	}
	&{$self->{train_end}} if $self->{train_end};
	return 1;
}

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

	# not implimented

	# Format input data
	foreach (@_){
		$self->_add_input_from_str($_);
	}
	return 1;
}


=head1 PRIVATE METHOD _select_target

Return a random target from the training set in the C<input> field,
unless the C<targeting> field is defined, when the targets are
iterated over.

=cut

sub _select_target { my $self=shift;
	if (not $self->{targeting}){
		return $self->{input}->[
			(int rand(scalar @{$self->{input}}))
		];
	}
	else {
		$self->{tar}++;
		if ($self->{tar}>$#{ $self->{input} }){
			$self->{tar} = 0;
		}

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

Enhancement factor: e.g. weight=3.  The training rate for the
corresponding input pattern vector is multiplied by this
parameter so that the reference vectors are updated as if this
input vector were repeated 3 times during training (i.e., as if
the same vector had been stored 2 extra times in the data file).

=item -

Fixed-point qualifier: e.g. fixed=2,5.  The map unit defined by
the fixed-point coordinates (x = 2; y = 5) is selected instead of
the best-matching unit for training. (See below for the definition
of coordinates over the map.) If several inputs are forced to
known locations, a wanted orientation results in the map.

=back

=back

Not (yet) implimented in file format: