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by drzaiusx11
11 days ago
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PCA (using eigenvectors for dimensionsional reduction) is kinda like moving the axis from an x/y/z grid and onto the shape itself. So it's not 2d in the sense of a simple projection where the loss of information is greater. It has a lot of useful applications, 3d shape recognition is just one. |
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