AI-FANN-Evolving
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lib/AI/FANN/Evolving.pm view on Meta::CPAN
}
);
my %constant;
for my $hashref ( values %enum ) {
while( my ( $k, $v ) = each %{ $hashref } ) {
$constant{$k} = $v;
}
}
my %default = (
'error' => 0.0001,
'epochs' => 5000,
'train_type' => 'ordinary',
'epoch_printfreq' => 100,
'neuron_printfreq' => 0,
'neurons' => 15,
'activation_function' => FANN_SIGMOID_SYMMETRIC,
);
=head1 NAME
lib/AI/FANN/Evolving.pm view on Meta::CPAN
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
Getter/setter to influence default ANN configuration
=cut
sub defaults {
my $self = shift;
my %args = @_;
for my $key ( keys %args ) {
$log->info("setting $key to $args{$key}");
if ( $key eq 'activation_function' ) {
$args{$key} = $constant{$args{$key}};
}
$default{$key} = $args{$key};
}
return %default;
}
sub _init {
my $self = shift;
my %args = @_;
for ( qw(error epochs train_type epoch_printfreq neuron_printfreq neurons activation_function) ) {
$self->{$_} = $args{$_} // $default{$_};
}
return $self;
}
=item clone
Clones the object
=cut
lib/AI/FANN/Evolving.pm view on Meta::CPAN
return $self->{'error'} = $value;
}
else {
$log->debug("getting error threshold");
return $self->{'error'};
}
}
=item epochs
Getter/setter for the number of training epochs, default is 500000
=cut
sub epochs {
my $self = shift;
if ( @_ ) {
my $value = shift;
$log->debug("setting training epochs to $value");
return $self->{'epochs'} = $value;
}
else {
$log->debug("getting training epochs");
return $self->{'epochs'};
}
}
=item epoch_printfreq
Getter/setter for the number of epochs after which progress is printed. default is 1000
=cut
sub epoch_printfreq {
my $self = shift;
if ( @_ ) {
my $value = shift;
$log->debug("setting epoch printfreq to $value");
return $self->{'epoch_printfreq'} = $value;
}
lib/AI/FANN/Evolving.pm view on Meta::CPAN
}
else {
$log->debug("getting neurons");
return $self->{'neurons'};
}
}
=item neuron_printfreq
Getter/setter for the number of cascading neurons after which progress is printed.
default is 10
=cut
sub neuron_printfreq {
my $self = shift;
if ( @_ ) {
my $value = shift;
$log->debug("setting neuron printfreq to $value");
return $self->{'neuron_printfreq'} = $value;
}
lib/AI/FANN/Evolving.pm view on Meta::CPAN
return $self->{'train_type'} = $value;
}
else {
$log->debug("getting train type");
return $self->{'train_type'};
}
}
=item activation_function
Getter/setter for the function that maps inputs to outputs. default is
FANN_SIGMOID_SYMMETRIC
=back
=cut
sub activation_function {
my $self = shift;
if ( @_ ) {
my $value = shift;
lib/AI/FANN/Evolving/Experiment.pm view on Meta::CPAN
=head1 NAME
AI::FANN::Evolving::Experiment - an experiment in evolving artificial intelligence
=head1 METHODS
=over
=item new
Constructor takes named arguments, sets default factory to L<AI::FANN::Evolving::Factory>
=cut
sub new { shift->SUPER::new( 'factory' => AI::FANN::Evolving::Factory->new, @_ ) }
=item workdir
Getter/Setter for the workdir where L<AI::FANN> artificial neural networks will be
written during the experiment. The files will be named after the ANN's error, which
needs to be minimized.
lib/AI/FANN/Evolving/Factory.pm view on Meta::CPAN
package AI::FANN::Evolving::Factory;
use strict;
use Algorithm::Genetic::Diploid;
use base 'Algorithm::Genetic::Diploid::Factory';
our $AUTOLOAD;
my %defaults = (
'experiment' => 'AI::FANN::Evolving::Experiment',
'chromosome' => 'AI::FANN::Evolving::Chromosome',
'gene' => 'AI::FANN::Evolving::Gene',
'traindata' => 'AI::FANN::Evolving::TrainData',
);
=head1 NAME
AI::FANN::Evolving::Factory - creator of objects
lib/AI/FANN/Evolving/Factory.pm view on Meta::CPAN
=item new
Constructor takes named arguments. Key is a short name (e.g. 'traindata'), value is a
fully qualified package name (e.g. L<AI::FANN::TrainData>) from which to instantiate
objects identified by the short name.
=back
=cut
sub new { shift->SUPER::new(%defaults,@_) }
1;
lib/AI/FANN/Evolving/TrainData.pm view on Meta::CPAN
=head1 NAME
AI::FANN::Evolving::TrainData - wrapper class for FANN data
=head1 METHODS
=over
=item new
Constructor takes named arguments. By default, ignores column
named ID and considers column named CLASS as classifier.
=cut
sub new {
my $self = shift->SUPER::new(
'ignore' => [ 'ID' ],
'dependent' => [ 'CLASS' ],
'header' => {},
'table' => [],
script/aivolver view on Meta::CPAN
'outfile=s' => \$outfile,
'initialize=s' => \%initialize,
'data=s' => \%data,
'experiment=s' => \%experiment,
'ann=s' => \%ann,
'help|?' => sub { pod2usage( '-verbose' => 1 ) },
'manual' => sub { pod2usage( '-verbose' => 2 ) },
);
# configure ANN
AI::FANN::Evolving->defaults(%ann);
# configure logger
my $log = Algorithm::Genetic::Diploid::Logger->new;
$log->level( 'level' => $verbosity );
$log->formatter( $formatter );
# read input data
my $deps = join ', ', @{ $data{'dependent'} };
my $ignore = join ', ', @{ $data{'ignore'} };
$log->info("going to read train data $data{file}, ignoring '$ignore', dependent columns are '$deps'");
script/aivolver view on Meta::CPAN
B<***NO LONGER ACCURATE, CONSULT THE YAML CONFIG FILES***>
=over
=item B<<config.ymlE<gt>>
If the first command line argument is a file location, this will be interpreted as the
location of a configuration file in YAML syntax structured as in this
example: L<https://raw.github.com/naturalis/ai-fann-evolving/master/examples/conf.yml>.
Subsequent command line arguments can then be provided that override the defaults in this
configuration file.
=item B<-h/--help/-?>
Prints help message and exits.
=item B<-m/--manual>
Prints manual page and exits.
$log->formatter(sub{
my %args = @_;
if ( $args{'msg'} =~ /fittest at generation (\d+): (.+)/ ) {
my ( $gen, $fitness ) = ( $1, $2 );
ok( $fitness, "generation $gen/2, fitness: $fitness" );
}
return '';
});
# set quieter and quicker to give up
AI::FANN::Evolving->defaults( 'epoch_printfreq' => 0, 'epochs' => 200 );
# instantiate factory
my $fac = new_ok('AI::FANN::Evolving::Factory');
# prepare data
my $data = AI::FANN::Evolving::TrainData->new(
'file' => "$Bin/../examples/Cochlopetalum.tsv",
'ignore' => [ 'image' ],
'dependent' => [ 'C1', 'C2', 'C3', 'C4', 'C5' ],
);
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