Factor Investing, Dimensionality Reduction, Sklearn, Python.
most significant variability, and so on. PCA involves finding the eigenvectors and eigenvalues of the covariance matrix or the correlation matrix of the data. The eigenvectors represent the directions or axes along which the data varies the most, and the eigenvalues represent the amount of