Neural Networks Learning
首先,我不得不说,这是我开始这门课程时做的最辛苦的练习。
1.3 Feedforward and cost function
1 | a1 = [ones(m, 1), X]; |
目前,我对I(y,:)
还是一头雾水,怎么能让 y(5000:1)变成 Y(5000:10),每行都有匹配指数?
1.4 Regularized cost function
1 | r = lambda/2/m * (sum(sum(Theta1(:,2:end).^2)) + sum(sum(Theta2(:,2:end).^2))); |
2.1 Sigmoid gradient
1 | g = sigmoid(z).*(1-sigmoid(z)); |
2.3 Backpropagation
$$\delta {k}^{(3)} = (a{k}^{(3)} - y_{k})$$
$$\dfrac{\partial }{\partial \Theta {ij}^{(l)}}J(\Theta ) = D{ij}^{(l)} = \dfrac{1}{m}\Delta _{ij}^{(l)}$$
1 | d3 = a3-Y; |
2.5 Regularized Neural Networks
1 | Theta1_grad(:,2:end) = Theta1_grad(:,2:end) + lambda/m*Theta1(:,2:end); |
The hidden layer
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