In what scenarios would you prefer LDA over PCA?
- When class labels are irrelevant
- When class separation is the priority
- When data is nonlinear
- When maximizing total variance is the priority
You would prefer LDA over PCA "when class separation is the priority." While PCA focuses on capturing the maximum variance, LDA aims to find the directions that maximize the separation between different classes.
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