Principal Component Analysis (PCA) is a fundamental tool for dimension reduction and exploratory analysis of multivariate data, yet standard implementations often provide limited support for ...

PCA is typically taught with formulas and static diagrams. This tool lets you manipulate parameters and immediately see how correlations affect data structure, how principal components emerge, and why ...