You can also use the python interface to pylearn2, rather than the yaml. If
you are interested in examples of the python interface for pylearn2, I have
some examples (I greatly prefer the python interface, but to each their
own):
https://github.com/kastnerkyle/pylearn2-practice/blob/master/cifar10_train.pyshows
how to build a network and test using a pylearn2 builtin dataset
https://github.com/kastnerkyle/kaggle-dogs-vs-cats/blob/master/kaggle_train.py
This shows how to use scikit-learn's train-test split to create training
and testing classes for new datasets in pylearn2 format. x and y are both
2D. Rows are samples, columns are features for x. y generally needs to be a
"one hot" label matrix for classification, but will be a regression target
for RMSE/regression tasks.
In general, it is pretty easy to wrap your data into a pylearn2 compatible
format, though doing "raw" input for convolutional nets can be tricky. I
have an example of reading pngs from Kaggle's CIFAR10 competition into
pylearn2 and using a convnet here:
https://github.com/kastnerkyle/kaggle-cifar10
All that being said, theano-nets *can* be easier to start with for those
who are new to neural networks, as it is a little less roll-your-own.
I have had success using both.
Kyle
On Mon, Apr 7, 2014 at 11:48 AM, Ralf Gunter <[email protected]> wrote:
> Two libraries[1,2] come to mind that can additionally support
> accelerators through opencl. Just take note that it can take a bit to
> familiarize yourself with pylearn2, especially because they seem
> adamant in doing everything through yaml scripts.
>
> [1] -- https://github.com/lmjohns3/theano-nets (see e.g.
> examples/xor-classfier.py)
> [2] -- http://deeplearning.net/software/pylearn2
>
> 2014-04-07 11:18 GMT-05:00 Yuxiang Wang <[email protected]>:
> > Dear all,
> >
> > I am not entirely sure whether this is the best place to post this,
> > and please do excuse me if this is not the perfect list for this
> > question.
> >
> > Is there any python packages for neural networks for regression
> > (instead of classification)?
> >
> > Any help would be appreciated. Thanks!
> >
> > -Shawn
> >
> >
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