Mathematics, Linear Algebra, Machine Learning, Data Science.
reduction is Principal Component Analysis (PCA). When we calculate the eigenvalues of a matrix, they reveal how much variance is captured by each eigenvector (principal component). In the context of dimensionality reduction, we aim to keep the eigenvectors with the highest eigenvalues, as these