What is the 'manifold hypothesis' and why is it important for unsupervised learning?
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A
It states that real-world data is always linearly separable in sufficiently high dimensions
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B
It posits that high-dimensional data lies on a lower-dimensional manifold, motivating nonlinear dimensionality reduction
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C
It claims that all clusters in real data have a Gaussian distribution
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D
It asserts that the number of meaningful features equals the square root of the sample size