【转载】Restricted Boltzmann Machines, and also Deep Belief Networks of stacked RBM's

This is a small library that can train Restricted Boltzmann Machines, and also Deep Belief Networks of stacked RBM's.

http://code.google.com/p/matrbm/

Train RBM's:

%train an RBM with binary visible units and 500 binary hidden model= rbmBB(data, 500);
%visualize the learned weights visualize(model.W);

Do classification:

model= rbmFit(data, 500, labels); prediction= rbmPredict(model, testdata);

Train a Deep Belief Network with 500,500,2000 architecture for classification:

models= dbnFit(data, [500 500 2000], labels); prediction= dbnPredict(models, testdata);

see included example code for more

I can be contacted on andrej.karpathy@ gmail.

NOTE: This was a class project that I worked on for 1 month and then abandoned development for almost 4 years ago. Please do not send me specific questions about issues with the code or questions on how to do something. I only put this code online in hope that it can be useful to others but cannot fully support it.

If you would like pointers to more actively maintained implementations, have a look here (https://github.com/rasmusbergpalm/DeepLearnToolbox) or maybe here (https://github.com/lisa-lab/DeepLearningTutorials)

Sorry and best of luck!