Exercise:PCA and Whitening
From Ufldl
(→PCA, PCA whitening and ZCA implementation) |
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You will build on the MATLAB starter code which we have provided in <tt>[http://ufldl.stanford.edu/wiki/resources/pca_exercise.zip pca_exercise.zip]</tt>. You need only write code at the places indicated by "YOUR CODE HERE" in the files. The only file you need to modify is <tt>pca_gen.m</tt>. | You will build on the MATLAB starter code which we have provided in <tt>[http://ufldl.stanford.edu/wiki/resources/pca_exercise.zip pca_exercise.zip]</tt>. You need only write code at the places indicated by "YOUR CODE HERE" in the files. The only file you need to modify is <tt>pca_gen.m</tt>. | ||
| - | === Step | + | === Step 0a: Load data === |
The starter code contains code to load some natural images and sample 10000 14x14 patches from them. The raw patches sampled from the images will look something like this: | The starter code contains code to load some natural images and sample 10000 14x14 patches from them. The raw patches sampled from the images will look something like this: | ||
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These patches are stored as column vectors <math>x^{(i)} \in \mathbb{R}^{196}</math> in the <math>196 \times 10000</math> matrix <math>x</math>. | These patches are stored as column vectors <math>x^{(i)} \in \mathbb{R}^{196}</math> in the <math>196 \times 10000</math> matrix <math>x</math>. | ||
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| + | === Step 0b: Zero mean the data === | ||
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| + | You should then zero-mean the data by subtracting the mean image from each image. | ||
=== Step 1: Implement PCA === | === Step 1: Implement PCA === | ||
