【deep learning学习笔记】注释yusugomori的DA代码 --- dA.h

DA就是“Denoising Autoencoders”的缩写。继续给yusugomori做注释，边注释边学习。看了一些DA的材料，基本上都在前面“转载”了。学习中间总有个疑问：DA和RBM到底啥区别？（别笑，我不是“学院派”的看Deep Learning理论，如果“顺次”看下来，可能不会有这个问题），现在了解的差不多了，详情见：【deep learning学习笔记】Autoencoder。之后，又有个疑问，DA具体的权重更新公式是怎么推导出来的？我知道是BP算法，不过具体公示的推导、偏导数的求解，没有看到哪个材料有具体的公式，所以姑且认为yusugomori的代码写的是正确的。

注释后的头文件：

// The Class of denoising auto-encoder
class dA
{
public:
int N;			// the number of training samples
int n_visible;	// the number of visible nodes
int n_hidden;	// the number of hidden nodes
double **W;		// the weight connecting visible node and hidden node
double *hbias;	// the bias of hidden nodes
double *vbias;	// the bias of visible nodes

public:
// initialize the parameters
dA ( int,		// N
int,		// n_visible
int ,		// n_hidden
double**,	// W
double*,	// hbias
double*	// vbias
);
~dA();

// make the input noised
void get_corrupted_input (
int*,		// the original input 0-1 vector			-- input
int*,		// the resulted 0-1 vector gotten noised	-- output
double		// the p probability of noise, binomial test -- input
);
// encode process: calculate the probability output from hidden node
// p(hi|v) = sigmod ( sum_j(vj * wij) + bi), it's same with RBM
// but different from RBM, it dose not generate 0-1 state from Bernoulli distribution
void get_hidden_values (
int*,		// the input from visible nodes
double*		// the output of hidden nodes
);
// decode process: calculate the probability output from visiable node
// p(vi|h) = sigmod ( sum_j(hj * wij) + ci), it's same with RBM
// but different from RBM, it dose not generate 0-1 state from Bernoulli distribution
void get_reconstructed_input (
double*,	// the input from hidden nodes
double*		// the output reconstructed of visible nodes
);
// train the model by a single sample
void train (
int*,		// the input sample from visiable node
double,		// the learning rate
double		// corruption_level is the probability of noise
);
// reconstruct the input sample
void reconstruct (
int*,		// the input sample		-- input
double*		// the reconstructed value -- output
);
};