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Which technique handles high-dimensional sparse data efficiently?
- Dimensionality Reduction
- Sparse Representations
- Both A and B
- Neither
Answer: Both A and B
High-dimensional handling: dimensionality reduction (PCA, autoencoders) compresses features; sparse representations (L1 regularization) select relevant features. Critical for text, recommendation systems.