Exercise:Self-Taught Learning
From Ufldl
(→Step Four: Training and testing the logistic regression model) |
(→Step Three: Training the logistic regression model) |
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Fill in <tt>feedForwardSparseAutoencoder.m</tt> to produce a matrix whose columns correspond to activation of the hidden layer for each example i.e. the vector <math>a^{(2)}</math> corresponding to activation of layer <math>L_{2}</math>. | Fill in <tt>feedForwardSparseAutoencoder.m</tt> to produce a matrix whose columns correspond to activation of the hidden layer for each example i.e. the vector <math>a^{(2)}</math> corresponding to activation of layer <math>L_{2}</math>. | ||
| - | After doing so, this step will use your modified function to convert the raw image data to feature unit activations. It will then train the softmax regression model on the hidden unit activation and labels with <tt> | + | After doing so, this step will use your modified function to convert the raw image data to feature unit activations. It will then train the softmax regression model on the hidden unit activation and labels with <tt>softmaxTrain.m</tt>. |
===Step Four: Training and testing the logistic regression model=== | ===Step Four: Training and testing the logistic regression model=== | ||
