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ML Foundations: PCA and Dimensionality Reduction

Advanced quiz on centering, covariance matrices, principal components, projections, explained variance, whitening, and SVD connections.

11 questionsEstimated 45 min0 flagged

Session status

Draft

Question 1

1 point(s)

What does PCA optimize?

Choose the best description of the first principal component.

It finds the direction of maximum projected variance

It finds the direction with the smallest norm

It minimizes the determinant of the covariance matrix

It guarantees the classes become linearly separable