[SciPy-User] Artificial Neural Network thoughts

Matthieu Brucher matthieu.brucher@gmail....
Sat Oct 30 05:50:09 CDT 2010


For machine learning stuff, you may want to check :
- scikits.learn
- ...


2010/10/30 Gerrit Holl <gerrit.holl@ltu.se>:
> Hi,
> Summary of e-mail: "There are so many ANN packages and none seem very
> good; which one should I choose?"
> I am in the process of a transition from using primarily Matlab™ to
> using Python and additional packages. I've been getting increasingly
> annoyed with Matlab™ for a long time for reasons I probably don't need
> to explain here. My colleagues often accuse OSS of being too instable;
> not in the sense that it crashes, but that API's change too often and
> code just breaks upon increasing versions. Indeed, to get a several
> years old Python package written by a former co-worker working, I
> spend some hours digging through the code, because scipy now requires
> explicit imports (see
> http://projects.scipy.org/scipy/changeset/5206/trunk/scipy/__init__.py
> ), and this package relied on "from scipy import *'. Not nice, I don't
> see a good reason why this should break. But as Matlab™ in its latest
> upgrade from 2010A to 2010B started to do the same (changing error
> identifiers, changing behaviour in neural network toolbox, both
> undocumented), I decided to go for Python. Of course, Python is not
> enough; for my work, I need at least numpy, scipy, matplotlib,
> ScientificPython, pytables (or another HDF5 interface), and a neural
> network toolkit.
> Many dependencies for my code, but alas, it works. I found more or
> less actively maintained packages that do what I need for all but the
> last toolkit. I need to train a regression, with neural networks or
> maybe other machine learning systems (support vector machines,
> bayesian monte carlo integration, ...). And frankly, I'm a bit worried
> about what's "out there". I like OSS, but here it appears considerably
> less strong than the propriety ANN package from Mathworks™,
> particularly when it comes to documentation. I am looking for advice.
> Is anyone using ANNs in production code, if so, what are the
> experiences? I have found:
> - Fast Artificial Neural Network Library (FANN), written in C but with
> Python bindings. Looks good, but appears to lack active maintenance.
> Version 2.1.0beta was published 2007-02-01 and the CVS repository
> appears unchanged for years. That doesn't sound good. Do I really want
> to rely on that?
> - bpnn.py, a 171 LOC lone pure Python file implementing
> back-propagation NN that "could use numpy to speed this up". Looks
> really simple and probably quite good to understand the concept, but
> is it any good for production code? Looks like I would need to do a
> lot of coding to make it fast (at least numpy-based) and tweak the
> settings. A Numeric-based implementation exists at
> http://www.dacya.ucm.es/jam/download.htm. It would probably take some
> time porting it to numpy.
> - ffnet, last (beta...) version published 2009-10-27 and last activity
> in svn tree 9 months ago. Seems allright, but is it stable? Is it
> maintained? Can I use it?
> - Monte Python appears to do neural networks. No idea how good it is.
> Last published version in June this year, verison 0.2.0, "introduces
> incompatibilities with previous versions" and was published more than
> 2 years after the version before.
> - pyann, http://sourceforge.net/projects/pyann/ "version 0.1.0"
> published in 2007 and last svn activity 4 months ago. Another one that
> seems really fragile.
> There are others. That is in fact a disadvantage. There are >5
> packages and as far as I can see none sticks out. Do I really have the
> time to try them all out? Different needs, different qualities. But
> active maintenance is something anyone will be interested in, I
> suppose. Hence my question:
> What experiences do people have in using Artificial Neural Networks in
> Python+friends? What packages are suitable for production code and can
> be more or less relied on without having to understand all the
> details? Is any package much more widely used than the others?
> Thoughts are welcome!
> regards,
> Gerrit.
> --
> Gerrit Holl
> PhD student at Department of Space Science, Luleå University of
> Technology, Kiruna, Sweden
> http://www.sat.ltu.se/members/gerrit/
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