AI-FANN-Evolving

 view release on metacpan or  search on metacpan

script/aivolver  view on Meta::CPAN

#!/usr/bin/perl
use strict;
use warnings;
use Pod::Usage;
use Getopt::Long;
use YAML::Any 'LoadFile';
use File::Path 'make_path';
use AI::FANN::Evolving;
use AI::FANN::Evolving::TrainData;
use Algorithm::Genetic::Diploid::Logger ':levels';

# initialize config variables
my $verbosity = WARN; # log level
my $formatter = 'simple'; # log formatter
my %initialize;       # settings to start the population
my %data;             # train and test data files
my %experiment;       # experiment settings
my %ann;              # ANN settings
my $outfile;

# there are no arguments
if ( not @ARGV ) {
	pod2usage( '-verbose' => 0 );
}

# first argument is a config file
if ( -e $ARGV[0] ) {
	my $conf = shift;
	my $yaml = LoadFile($conf);
	$outfile    = $yaml->{'outfile'}         if defined $yaml->{'outfile'};
	$verbosity  = $yaml->{'verbosity'}       if defined $yaml->{'verbosity'};
	$formatter  = $yaml->{'formatter'}       if defined $yaml->{'formatter'};
	%initialize = %{ $yaml->{'initialize'} } if defined $yaml->{'initialize'};
	%data       = %{ $yaml->{'data'} }       if defined $yaml->{'data'};
	%experiment = %{ $yaml->{'experiment'} } if defined $yaml->{'experiment'};
	%ann        = %{ $yaml->{'ann'} }        if defined $yaml->{'ann'};
}

# process command line arguments
GetOptions(
	'verbose+'     => \$verbosity,
	'formatter=s'  => \$formatter,
	'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'");
my $inputdata = AI::FANN::Evolving::TrainData->new(
	'file'      => $data{'file'},
	'dependent' => $data{'dependent'},
	'ignore'    => $data{'ignore'},
);
my ( $traindata, $testdata );
if ( $data{'type'} and lc $data{'type'} eq 'continuous' ) {
	( $traindata, $testdata ) = $inputdata->sample_data( $data{'fraction'} );
}
else {
	( $traindata, $testdata ) = $inputdata->partition_data( $data{'fraction'} );
}



( run in 0.605 second using v1.01-cache-2.11-cpan-0bb4e1dffa6 )