Principal component analysis (PCA) is a classical machine learning technique. The goal of PCA is to transform a dataset into one with fewer columns. This is called dimensionality reduction. The ...
If you have a matrix A with dim = n, it is possible to compute n eigenvalues (ordinary numbers like 1.234) and n associated eigenvectors, each with n values. You can think of eigenvalues and their ...
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