【文件属性】:
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)
网友评论
- 感谢分享,可以直接使用。
- 还不错学习了
- 代码不错,通俗易懂,值得学习
- 学习学习,初学者的感觉
- 运行有错啊
- 非常好的资源,可以很好的学习rbm学习过程。对初学者很有帮助,无论是matlab初学者还是深度学习初学者
- 可以用,不过发现机器学习入门好难
- 代码不错,可以用,准确率92%
- 解释挺详细,自己的数据分类效果很差,没太看明白顶层用的什么分类原理
- 代码写得不错
- 代码写的很不错,初学者很好的教材
- 代码写得不错,初学ing
- 这个RBM的代码写的很好,对初学者很有帮助,注释也很详细