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Principal Component Analysis (PCA)

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<strong>PCA</strong> for data compression<br />

What if you wanted to transmit someone’s height and weight,<br />

but you could only give a single number?<br />

• Could give only height, x<br />

— = (uncertainty when height is known)<br />

• Could give only weight, y<br />

— = (uncertainty when weight is known)<br />

• Could give only c 1 ,<br />

the value of first PC<br />

— = (uncertainty when first PC is known)<br />

• Giving the first PC minimizes<br />

the squared error of the result.<br />

weight<br />

Jochen Triesch, UC San Diego, http://cogsci.ucsd.edu/~triesch 16<br />

y<br />

PC2<br />

To compress n-dimensional data into k dimensions, order the<br />

principal components in order of largest-to-smallest<br />

eigenvalue, and only save the first k components.<br />

c 2<br />

x<br />

c 1<br />

PC1<br />

height

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