11/17 Notes
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HW 3 due December 1st

Project 3 due December 16th

Quiz 3 sometime

Can take quiz 4 if you want, takes top 3 quizzes

PCA
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Face images can be denoted as a point in high dimentional space (d x 1)

Each eigenvector is known as a PC

Eigenvectors pivot in center of image points

face image = f

f = weight_1 x eigenvector_1 + weight_2 x eigenvector_2 + ... + weight_d x eigenvector_d

See notes from tuesday

LDA
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Each subject has a label, PCA does not do this

In LDA you want the subjects seperated

The only difference between PCA and LDA is how we compute Covarience matrix
(calculate 2 of them in LDA)

Sw and SB are the 2 Cov matricies