文件名称：RBM代码实现MATLAB
文件大小：2.79MB
文件格式：RAR
更新时间：2018-04-19 03:43:48
RBM
This is a small library that can train Restricted Boltzmann Machines, and also Deep Belief Networks of stacked RBM's. 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! 原文：http://code.google.com/p/matrbm/
【文件预览】：
RBMLIB
----readme.docx(13KB)
----mnist_classify.mat(2.84MB)
----examplecode.m(2KB)
----RBM()
--------nunique.m(977B)
--------dbnFit.m(2KB)
--------rbmVtoH.m(355B)
--------process_options.m(4KB)
--------rbmHtoV.m(358B)
--------prepareArgs.m(690B)
--------logistic.m(65B)
--------softmax_sample.m(371B)
--------dbnPredict.m(495B)
--------rbmPredict.m(877B)
--------interweave.m(409B)
--------rbmBB.m(5KB)
--------visualize.m(750B)
--------softmaxPmtk.m(286B)
--------rbmFit.m(6KB)