| Principal Component Analysis: Transform features to a new space in which the features are uncorrelated. |
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| Linear Discriminant Analysis: Projection of d-dimensional data onto a line; Dimensionality reduction by mapping L distributions to (L-1)-dimensional subspace; maximize class separability. |
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