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NOTE: Debugging verbosity has been toned down somewhat from AI::NeuralNet::BackProp,
but level 4 still prints the same amount of information as you were used to. The other
levels, however, are mostly for  advanced use. Not much explanation in the other
levels, but they are included for those of you that feel daring (or just plain bored.)

Level 0 ($level = 0) : Default, no debugging information printed. All printing is 
left to calling script.

Level 1 ($level = 1) : Displays the activity between nodes, prints what values were
received and what they were weighted to.

Level 2 ($level = 2) : Just prints info from the learn() loop, in the form of "got: X, wanted Y"
type of information. This is about the third most useful debugging level, after level 12 and
level 4.

Level 3 ($level = 3) : I don't think I included any level 3 debugs in this version.

Level 4 ($level = 4) : This level is the one I use most. It is only used during learning. It
displays the current error (difference between actual outputs and the target outputs you
asked for), as well as the current loop number and the benchmark time for the last learn cycle.
Also printed are the actual outputs and the target outputs below the benchmark times.

Level 12 ($level = 12) : Level 12 prints a dot (period) [.] after each learning loop is
complete. This is useful for letting the user know that stuff is happening, but without
having to display any of the internal variables. I use this in the ex_aln.pl demo,
as well as the ex_agents.pl demo.

Toggles debuging off when called with no arguments. 



=item $net->save($filename);

This will save the complete state of the network to disk, including all weights and any
words crunched with crunch() . Also saves the layer size and activations of the network.

NOTE: The only activation type NOT saved is the CODE ref type, which must be set again
after loading.

This uses a simple flat-file text storage format, and therefore the network files should
be fairly portable.

This method will return undef if there was a problem with writing the file. If there is an
error, it will set the internal error message, which you can retrive with the error() method,
below.

If there were no errors, it will return a refrence to $net.


=item $net->load($filename);

This will load from disk any network saved by save() and completly restore the internal
state at the point it was save() was called at.

If the file is of an invalid file type, then load() will
return undef. Use the error() method, below, to print the error message.

If there were no errors, it will return a refrence to $net.

UPDATE: $filename can now be a newline-seperated set of mesh data. This enables you
to do $net->load(join("\n",<DATA>)) and other fun things. I added this mainly
for a demo I'm writing but not qutie done with yet. So, Cheers!



=item $net->activation($layer,$type);

This sets the activation type for layer C<$layer>.

C<$type> can be one of four values:

	linear                    ( simply use sum of inputs as output )
	sigmoid    [ sigmoid_1 ]  ( only positive sigmoid )
	sigmoid_2                 ( positive / 0 /negative sigmoid )
	\&code_ref;

"sigmoid_1" is an alias for "sigmoid". 

The code ref option allows you to have a custom activation function for that layer.
The code ref is called with this syntax:

	$output = &$code_ref($sum_of_inputs, $self);
	
The code ref is expected to return a value to be used as the output of the node.
The code ref also has access to all the data of that node through the second argument,
a blessed hash refrence to that node.

See CUSTOM ACTIVATION FUNCTIONS for information on several included activation functions
other than the ones listed above.

The activation type for each layer is preserved across load/save calls. 

EXCEPTION: Due to the constraints of Perl, I cannot load/save the actual subs that the code
ref option points to. Therefore, you must re-apply any code ref activation types after a 
load() call.

=item $net->node_activation($layer,$node,$type);

This sets the activation function for a specific node in a layer. The same notes apply
here as to the activation() method above.


=item $net->threshold($layer,$value);

This sets the activation threshold for a specific layer. The threshold only is used
when activation is set to "sigmoid", "sigmoid_1", or "sigmoid_2". 


=item $net->node_threshold($layer,$node,$value);

This sets the activation threshold for a specific node in a layer. The threshold only is used
when activation is set to "sigmoid", "sigmoid_1", or "sigmoid_2".  

=item $net->join_cols($array_ref,$row_length_in_elements,$high_state_character,$low_state_character);

This is more of a utility function than any real necessary function of the package.
Instead of joining all the elements of the array together in one long string, like join() ,
it prints the elements of $array_ref to STDIO, adding a newline (\n) after every $row_length_in_elements
number of elements has passed. Additionally, if you include a $high_state_character and a $low_state_character,
it will print the $high_state_character (can be more than one character) for every element that
has a true value, and the $low_state_character for every element that has a false value.