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CS 790Q Biometrics

2. Principal Component Analysis (PCA). Pattern recognition in high-dimensional spaces. Problems arise when performing recognition in a high-dimensional space (curse of dimensionality).Significant improvements can be achieved by first mapping the data into a lower-dimensional sub-space.. The goal of PCA is to reduce the dimensionality of the data while retaining as much as possible of the variation present in the original dataset..

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CS 790Q Biometrics

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