In the context of PCA, what is the role of Eigenvectors?
- Normalizing the data
- Representing noise in the data
- Representing outliers in the data
- Representing the direction of maximum variance
Eigenvectors in PCA represent the direction of maximum variance in the data. They define the directions along which the original data is projected to create the principal components.
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