view release on metacpan or  search on metacpan

BackProp.pm  view on Meta::CPAN

	print $net->learn(\@map,\@res);
	

If you call "$net->debug(4)" with $net being the 
refrence returned by the new() constructor, you will get benchmarking 
information for the learn function, as well as plenty of other information output. 
See notes on debug() in the METHODS section, below. 

If you do call $net->debug(1), it is a good 
idea to point STDIO of your script to a file, as a lot of information is output. I often
use this command line:

	$ perl some_script.pl > .out

Then I can simply go and use emacs or any other text editor and read the output at my leisure,
rather than have to wait or use some 'more' as it comes by on the screen.

=head2 METHODS

=over 4

docs.htm  view on Meta::CPAN

to view the learning stats for every learn call, you can just:
</P>
<PRE>
        print $net-&gt;learn(\@map,\@res);</PRE>
<P>If you call ``$net-&gt;debug(4)'' with $net being the 
refrence returned by the <CODE>new()</CODE> constructor, you will get benchmarking 
information for the learn function, as well as plenty of other information output. 
See notes on <A HREF="#item_debug"><CODE>debug()</CODE></A> in the METHODS section, below.</P>
<P>If you do call $net-&gt;debug(1), it is a good 
idea to point STDIO of your script to a file, as a lot of information is output. I often
use this command line:</P>
<PRE>
        $ perl some_script.pl &gt; .out</PRE>
<P>Then I can simply go and use emacs or any other text editor and read the output at my leisure,
rather than have to wait or use some 'more' as it comes by on the screen.</P>
<P>
<H2><A NAME="methods">METHODS</A></H2>
<DL>
<DT><STRONG><A NAME="item_BackProp">new AI::NeuralNet::BackProp($layers, $size [, $outputs, $topology_flag])</A></STRONG><BR>
<DD>
Returns a newly created neural network from an <CODE>AI::NeuralNet::BackProp</CODE>