DeepLearning 工具包DeepLearnToolbox 的使用

DeepLearn Toolbox是一個非常有用的matlab deep learning工具包，下載地址：https://github.com/dupuleng/DeepLearnToolbox-master

要使用它首先要將該工具包添加到matlab的搜索路徑中，

1、將包復制到matlab 的toolbox中，作者的路徑是D:\program Files\matlab\toolbox\

2、在matlab的命令行中輸入：　　

cd D:\program Files\matlab\toolbox\deepLearnToolbox\
addpath(gepath('D:\program Files\matlab\toolbox\deepLearnToolbox-master\')
savepath   %保存，這樣就不需要每次都添加一次

3、驗證添加是否成功，在命令行中輸入  

which saesetup

如果成功就會出現，saesetup.m的路徑D:\program Files\matlab\toolbox\deepLearnToolbox-master\SAE\saesetup.m 

4、使用deepLearnToolbox

load mnist_uint8;

train_x = double(train_x)/255;
test_x  = double(test_x)/255;
train_y = double(train_y);
test_y  = double(test_y);

%%  ex1 train a 100 hidden unit SDAE and use it to initialize a FFNN
%  Setup and train a stacked denoising autoencoder (SDAE)
rand('state',0)
sae = saesetup([784 100]);
sae.ae{1}.activation_function       = 'sigm';
sae.ae{1}.learningRate              = 1;
sae.ae{1}.inputZeroMaskedFraction   = 0.5;
opts.numepochs =   1;
opts.batchsize = 100;
sae = saetrain(sae, train_x, opts);
visualize(sae.ae{1}.W{1}(:,2:end)')

% Use the SDAE to initialize a FFNN
nn = nnsetup([784 100 10]);
nn.activation_function              = 'sigm';
nn.learningRate                     = 1;
nn.W{1} = sae.ae{1}.W{1};

% Train the FFNN
opts.numepochs =   1;
opts.batchsize = 100;
nn = nntrain(nn, train_x, train_y, opts);
[er, bad] = nntest(nn, test_x, test_y);
assert(er < 0.16, 'Too big error');