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lib/AI/NNFlex/Backprop.pm  view on Meta::CPAN

The Fahlman constant modifies the slope of the error curve. 0.1 is the standard value for everything, and speeds the network up immensely. If no Fahlman constant is set, the network will default to 0.1

=head2 AI::NNFlex::Dataset

 new (	[[INPUT VALUES],[OUTPUT VALUES],
	[INPUT VALUES],[OUTPUT VALUES],..])

=head2 INPUT VALUES

These should be comma separated values. They can be applied to the network with ::run or ::learn

=head2 OUTPUT VALUES
	
These are the intended or target output values. Comma separated. These will be used by ::learn


=head1 METHODS

This is a short list of the main methods implemented in AI::NNFlex::Backprop.

lib/AI/NNFlex/Hopfield.pm  view on Meta::CPAN

=head2 AI::NNFlex::Hopfield->new();

=head2 AI::NNFlex::Dataset

 new (	[[INPUT VALUES],[INPUT VALUES],
	[INPUT VALUES],[INPUT VALUES],..])

=head2 INPUT VALUES

These should be comma separated values. They can be applied to the network with ::run or ::learn

=head2 OUTPUT VALUES
	
These are the intended or target output values. Comma separated. These will be used by ::learn


=head1 METHODS

This is a short list of the main methods implemented in AI::NNFlex::Hopfield.