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lib/AI/FANN/Evolving.pm  view on Meta::CPAN

	return $value;
}

sub _list_properties {
	(
#		cascade_activation_functions   => 'activationfunc',
		cascade_activation_steepnesses => \&_mutate_double,
	)
}

sub _layer_properties {
	(

lib/AI/FANN/Evolving.pm  view on Meta::CPAN

		quickprop_mu                         => \&_mutate_double,
		rprop_increase_factor                => \&_mutate_double,
		rprop_decrease_factor                => \&_mutate_double,
		rprop_delta_min                      => \&_mutate_double,
		rprop_delta_max                      => \&_mutate_double,
		cascade_output_change_fraction       => \&_mutate_double,
		cascade_candidate_change_fraction    => \&_mutate_double,
		cascade_output_stagnation_epochs     => \&_mutate_int,
		cascade_candidate_stagnation_epochs  => \&_mutate_int,
		cascade_max_out_epochs               => \&_mutate_int,
		cascade_max_cand_epochs              => \&_mutate_int,
		cascade_num_candidate_groups         => \&_mutate_int,
		bit_fail_limit                       => \&_mutate_double, # 'fann_type',
		cascade_weight_multiplier            => \&_mutate_double, # 'fann_type',
		cascade_candidate_limit              => \&_mutate_double, # 'fann_type',
	)
}

=item defaults

lib/AI/FANN/Evolving.pm  view on Meta::CPAN

=cut

sub train {
	my ( $self, $data ) = @_;
	if ( $self->train_type eq 'cascade' ) {
		$log->debug("cascade training");
	
		# set learning curve
		$self->cascade_activation_functions( $self->activation_function );
		
		# train
		$self->{'ann'}->cascadetrain_on_data(
			$data,
			$self->neurons,
			$self->neuron_printfreq,
			$self->error,
		);

lib/AI/FANN/Evolving.pm  view on Meta::CPAN

	}
}

=item train_type

Getter/setter for the training type: 'cascade' or 'ordinary'. Default is ordinary

=cut

sub train_type {
	my $self = shift;

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=item $ann->train_on_data($train_data, $max_epochs, $epochs_between_reports, $desired_error)

C<$train_data> is a AI::FANN::TrainData object.

=item $ann->cascadetrain_on_file($filename, $max_neurons, $neurons_between_reports, $desired_error)

-

=item $ann->cascadetrain_on_data($train_data, $max_neurons, $neurons_between_reports, $desired_error)

C<$train_data> is a AI::FANN::TrainData object.

=item $ann->train_epoch($train_data)

lib/AI/FANN.pm  view on Meta::CPAN

=item $ann->print_parameters

-

=item $ann->cascade_activation_functions()

returns a list of the activation functions used for cascade training.

=item $ann->cascade_activation_functions(@activation_functions)

sets the list of activation function to use for cascade training.

=item $ann->cascade_activation_steepnesses()

returns a list of the activation steepnesses used for cascade training.

=item $ann->cascade_activation_steepnesses(@activation_steepnesses)

sets the list of activation steepnesses to use for cascade training.

=item $ann->training_algorithm

=item $ann->training_algorithm($training_algorithm)

lib/AI/FANN.pm  view on Meta::CPAN

=item $ann->bit_fail

-

=item cascade_output_change_fraction

=item cascade_output_change_fraction($fraction)

-

=item $ann->cascade_output_stagnation_epochs

=item $ann->cascade_output_stagnation_epochs($epochs)

-

=item $ann->cascade_candidate_change_fraction

=item $ann->cascade_candidate_change_fraction($fraction)

-

=item $ann->cascade_candidate_stagnation_epochs

=item $ann->cascade_candidate_stagnation_epochs($epochs)

-

=item $ann->cascade_weight_multiplier

=item $ann->cascade_weight_multiplier($multiplier)

-

=item $ann->cascade_candidate_limit

=item $ann->cascade_candidate_limit($limit)

-

=item $ann->cascade_max_out_epochs

=item $ann->cascade_max_out_epochs($epochs)

-

=item $ann->cascade_max_cand_epochs

=item $ann->cascade_max_cand_epochs($epochs)

-

=item $ann->cascade_num_candidates

-

=item $ann->cascade_num_candidate_groups

=item $ann->cascade_num_candidate_groups($groups)

-

=item $ann->neuron_activation_function($layer_index, $neuron_index)