PCA
From Ufldl
(→Example and Mathematical Background) |
(→Example and Mathematical Background) |
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the second eigenvector. | the second eigenvector. | ||
| - | + | Note: If you are interested in seeing a more formal mathematical derivation/justification of this result, see the CS229 (Machine Learning) lecture notes on PCA (link at bottom of this page). You won't need to do so to follow along this course, however. | |
You can use standard numerical linear algebra software to find these eigenvectors (see Implementation Notes). | You can use standard numerical linear algebra software to find these eigenvectors (see Implementation Notes). | ||
