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 ...
Load data into memory Normalize the data Apply singular value decomposition to the normalized data Compute eigenvalues and eigenvectors from the SVD results Sort the eigenvectors based on eigenvalues ...
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