Unsupervised Learning, Complex Systems, Principal Component, Dimensionality Reduction, Emergence.
configuration space. They are determined by an eigenvector and eigenvalue problem [1]. Where XᵗX is equivalent to the covariance matrix. I won’t go into detail, but there’s something really interesting happening here. By keeping only the first principal components, PCA is an efficient