AI-NNEasy
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lib/AI/NNEasy/NN.pm view on Meta::CPAN
#############################################################################
## This file was generated automatically by Class::HPLOO/0.21
##
## Original file: ./lib/AI/NNEasy/NN.hploo
## Generation date: 2005-01-16 19:51:58
##
## ** Do not change this file, use the original HPLOO source! **
#############################################################################
#############################################################################
## Name: NN.pm
## Purpose: AI::NNEasy::NN
## Author: Graciliano M. P.
## Modified by:
## Created: 2005-01-14
## RCS-ID:
## Copyright: (c) 2005 Graciliano M. P.
## Licence: This program is free software; you can redistribute it and/or
## modify it under the same terms as Perl itself
##
## This class and classes inside AI::NNEasy::NN::* were 1st based in the
## module AI::NNFlex from Charles Colbourn <charlesc at nnflex.g0n.net>.
##
#############################################################################
{ package AI::NNEasy::NN ;
use strict qw(vars) ; no warnings ;
use vars qw(%CLASS_HPLOO @ISA $VERSION) ;
$VERSION = '0.06' ;
@ISA = qw(Class::HPLOO::Base UNIVERSAL) ;
my $CLASS = 'AI::NNEasy::NN' ; sub __CLASS__ { 'AI::NNEasy::NN' } ;
use Class::HPLOO::Base ;
use AI::NNEasy::NN::layer ;
use AI::NNEasy::NN::feedforward ;
use AI::NNEasy::NN::backprop ;
use vars qw($AUTOLOAD) ;
sub NN {
my $this = ref($_[0]) ? shift : undef ;
my $CLASS = ref($this) || __PACKAGE__ ;
my $params = shift(@_) ;
my $netParams = shift(@_) ;
my @layers ;
foreach my $i (keys %$netParams) {
$this->{$i} = $$netParams{$i};
}
$this->{networktype} ||= 'feedforward' ;
$this->{learning_algorithm} ||= 'backprop' ;
$this->{learning_algorithm_class} = "AI::NNEasy::NN::" . $this->{learning_algorithm} ;
my $nntype_class = "AI::NNEasy::NN::" . $this->{networktype} . '_' . $this->{learning_algorithm} ;
bless($this , $nntype_class) ;
( run in 1.069 second using v1.01-cache-2.11-cpan-39bf76dae61 )