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CHANGES  view on Meta::CPAN

0.24
20050620

Fixed a bug in the implementation of bias weights. Implemented
the addition example.

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0.23
20050424

changed sigmoid to sigmoid2 in mathlib - this is a sigmoid
function generally used in BPTT, which isn't yet implemented.

Replaced with a more standard 1/1+exp(1)**-x function.

Implemented Hopfield module.

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0.22
XXXXXXXXX

implemented node & layer connect methods, to allow recurrent
connections.

put sigmoid_slope function in mathlib, courtesy of frodo72
@ perlmonks

Implemented functions to save & load snns .pat files in Dataset

Altered Dataset constructor to allow an empty param set - you
can now construct a null Dataset & add items to it using the
$dataset->add([[0,1],[1]) method (also implemented in this 
version.

Altered feedforward run method to return output pattern - more
intuitive that way.

Implemented a Hopfield module. This is very much the first cut
at this, since I've never really used hopfield nets before, and
haven't put any debug in etc, until I've rethought the whole
approach to debug in this set of code.

Implemented dataset->delete method.

Put the pod documentation back in Dataset.pm :-)


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0.21
20050313

Rewrote all the pod. Its probably a bit sparse now, but its 
much more accurate.

Removed the eval calls from feedforward, backprop & momentum
for speed.

Implemented fahlman constant. This eliminates the 'flat spot'
problem, and gets the network to converge more reliably. XOR
seems to never get stuck with this set to 0.1. as a bonus, its 
also about 50% faster (do you sense a theme developing here?)

Removed momentum module (well, removed backprop module and 
renamed momentum module in fact). There were few code differences
and its easier to maintain this way. Default option is vanilla
backprop, momentum & fahlman adjustments are only implemented if
specified in the network config.

Bundled all the maths functions into AI::NNFlex::Mathlib

Implemented calls to error transformation function, as per
Fahlman. Testing, it doesn't seem to make much difference, but
at least now the facility is there.

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0.20
20050308

v0.17 was never released, as I rejigged the whole lot for
object inheritance before I got around to uploading it to CPAN.
Why? I hear you ask, when it worked OK already.
1) its faster, a lot faster.
2) feedforward isn't the only kind of network, and I wanted to
be free to overload some of the methods (especially init) to
simplify writing a Hopfield module (in progress)
3) its more theoretically correct

So now, AI::NNFlex is the base class for the other types of 
networks, and you should never need to call AI::NNFlex class
directly - you should call the constructor of the subclass, such
as:
my $network = AI::NNFlex::momentum->new(params);

The upshot of that is that the network type and learning algorithm
parameters are now obsolete.

###

Removed draw.pm from the distribution - it really wasn't very useful
and hadn't been kept up to date with newer revisions of the code. It
will be put back later (perhaps) or incorporated into a separate GUI
frontend.

Removed feedforward_pdl.pm from the distribution - it shouldn't have
been there in the first place!

Fixed the lesion subs so they expect parameter=>value pairs instead
of an anonymous hash (left over from when I didn't know you could do
that).

Fixed an error - random weights was bounded by 1, not the parameter
'randomweights'. Its now positive only. Some benchmarking needed as
it appears that positive random starting weights rather than a mix
of positive and negative make the network quicker to converge, at
least with momentum.

weights now defaults to rand(1) instead of 0 - at least for backprop
type nets, a default 0 weight will never work. For other types of nets
the random weights can be overridden with the 'fixedweights' parameter.

CHANGES  view on Meta::CPAN

This version introduces a new, friendlier constructor. Instead
of the pair of anonymous hashes previously required, the 
constructor now takes fairly normal looking parameters. Layers
are added to a network using the add_layer method. This combines
a more intuitive approach with more flexibility.
The original constructor is not deprecated. Parameter names with
spaces in on the other hand ('activation function') are. They
should be replaced by the same parameter name without any spaces.
The new constructor will convert old format parameter names, but
its at the users risk.
See xor.pl or the perldoc & readme for examples.

Cleaned up the perldoc some more. Commented out all the method
perldocs, so there is just the single block defining the 
distributions documentation, as advocated by perlmonks. Method
perldocs in importable modules have not been commented out.

Removed the weight bounding in backprop & momentum. If the network
is going into an unstable state the weight bounding won't help,
and it causes errors under perl -w.

Implemented tests (apologies to the CPAN testers for not having
done so before!).


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0.13
20050121

New plugin training algorithm - momentum.pm
Improvement in speed using momentum on xor as follows (epochs)
mom 0.6
334
288
124
502
7433
avg=1736.2

no mom
641
718
20596
19964
660
avg=8515.8

Significant, I think you'll agree!

Fixed a bug that allowed training to proceed even if the activation
function (s) can't be loaded.

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0.12
20050116

Fixed a bug in reinforce.pm reported by G M Passos
Inserted a catch in feedforward->run to call datasets if the syntax

$network->run($dataset) is called.

Strictly speaking this doesn't fit with the design, but its likely to
be used quite a bit so its worth catching


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0.11
20050115
Added PNG support to AI::NNFlex::draw

Added AI::NNFlex::Dataset
This creates a dataset object that can be run against a
network

Added AI::NNFlex::lesion
Damages a network with a probability of losing a node
or a connection. See the perldoc

Cleaned up the POD docs a bit, although theres a lot still
to do.

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