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Results tagged with pca
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user 21958
Principal component analysis (PCA) is a linear dimensionality reduction technique. It reduces a multivariate dataset to a smaller set of constructed variables preserving as much information (as much variance) as possible. These variables, called principal components, are linear combinations of the input variables.
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Why does doing LDA on a outer product of input matrix gives same result as doing PCA of the ...
Why does doing Linear Discrimenant Analysis (LDA) on a outer product of input matrix gives same result as doing Principal Component Analysis (PCA) of the input matrix? … Not exactly sure where this came from and why it works, but the outer product of the input matrix $X^T X$
In PCA they use it to make the matrix square, so they can perform linear discrimant analysis on …
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