I'm a bit confused about the visualization of the weights of a feed forward neural network as provided in this example from scikit-learn. The network has an architecture of
[784 x 50 x 10] (MNIST dataset), so
n_hidden = 50 (there are 50 hidden units). Each of the hidden units is a column of the weight matrix
W_1 (with dimension 784x50), right? From this, I thought, we could create
50 images, each of size 28x28 (=784). However, there are only 16 images shown? What is my mistake here?
Since someone downvoted the question without explanation, here is what I assume. In the particular example stated above, one could acutally draw 50 pictures. Visualizing only 16 filters (4x4) was choosen for convenience.