Exercise:Self-Taught Learning
From Ufldl
(→Step 3: Extracting features) |
(→Step 3: Extracting features) |
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After the sparse autoencoder is trained, you will use it to extract features from the handwritten digit images. | After the sparse autoencoder is trained, you will use it to extract features from the handwritten digit images. | ||
- | Complete <tt>feedForwardAutoencoder.m</tt> to produce a matrix whose columns correspond to | + | Complete <tt>feedForwardAutoencoder.m</tt> to produce a matrix whose columns correspond to activations of the hidden layer for each example, i.e., the vector <math>a^{(2)}</math> corresponding to activation of layer 2. (Recall that we treat the inputs as layer 1). |
After completing this step, calling <tt>feedForwardAutoencoder.m</tt> should convert the raw image data to hidden unit activations <math>a^{(2)}</math>. | After completing this step, calling <tt>feedForwardAutoencoder.m</tt> should convert the raw image data to hidden unit activations <math>a^{(2)}</math>. |