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 ...

Notice that the SVD_Jacobi () function is applied to the transpose of stdX, which has shape 4-by-9. Most SVD implementations assume the data is arranged so that the number of rows is less than the ...