view release on metacpan or  search on metacpan

LICENSE  view on Meta::CPAN

The MIT License (MIT)

Copyright (c) 2014 Naturalis Biodiversity Center

Permission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in
the Software without restriction, including without limitation the rights to
use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
the Software, and to permit persons to whom the Software is furnished to do so,
subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER

script/aivolver  view on Meta::CPAN

=over

=item B<ID>

The C<ID> column contains a unique identifier (a string) for each record in the data set.

=item B<CLASS>

Each C<CLASS> column (multiple are allowed) specifies the classification that should
emerge from one of the output neurons. Often this would be an integer, for example
either C<1> or C<-1> for a binary classification. The number of C<CLASS> columns
determines the number of outputs in the ANN.

=item B<[others]>

All other columns are interpreted as the predictor columns from which the ANN must
derive its capacity for classification. Normally these are continuous values, which
are normalized between all records, e.g. in a range between -1 and 1.

=back

t/02-data.t  view on Meta::CPAN

use FindBin qw($Bin);
use Test::More 'no_plan';
use AI::FANN::Evolving::TrainData;
use Algorithm::Genetic::Diploid::Logger ':levels';
use Data::Dumper;

# instantiate a data object
my $file = "$Bin/../examples/merged.tsv";
my $data = AI::FANN::Evolving::TrainData->new( 
	'file'      => $file,
	'ignore'    => [ 'image' ],
	'dependent' => [ 'C1', 'C2', 'C3', 'C4' ],
);
ok( $data, "instantiate" );

# partition the data
my ( $d1, $d2 ) = $data->partition_data(0.2);
ok( $data->size == $d1->size + $d2->size, "partition" );