ex4.m
implement the backpropagation algorithm for neural networks and apply it to the task of hand-written digit recognition.
- Plot Data (in ex4data1.mat)
- Feedforward Using Neural Network and Compute Cost at parameters (loaded from ex4weights)
- Cost function with regularization
lambda: 1
- Random initialization weights
symmetry breaking: initialize weights
Theta(j, i) = RABD_NUM*(2*INIT_EPSILON) - INIT_EPSILON
RABD_NUM: between 0 to 1
- Complete backpropagation and check Neural Network Gradients
generate some ‘random’ test data and test
input_layer_size: 3
hidden_layer_size: 5
num_labels: 3
m: 5
- Regularized Neural Networks
lambda: 3
- Training Neural Network
lambda: 1
- Visualizing Weights
displaying the hidden units to see what features they are capturing in the data.
displaying images of Theta1
