What is the relationship between PCA and SVD?

Subject: Machine Learning

Topic: Statistical Learning and Feature Engineering

Options:

1. Option A: They are completely different techniques with no relationship.
2. Option B: PCA can be performed using SVD on the data matrix.
3. Option C: SVD is a type of PCA.
4. Option D: PCA is used only for classification, SVD for regression.

Correct Answer:

Option B: PCA can be performed using SVD on the data matrix.

Explanation:

PCA can be computed using SVD on the centered data matrix. The singular vectors from SVD correspond to the principal components, and the singular values relate to the variance explained.