Subpages (12): Classification with Normal Densities Ellipses, Gaussians, Convariances Introduction Invariances, PCA Kernel Density Estimation kNN Methods Multilayer Perceptrons Nearest Neighbor Classification Parameter Estimation PCA, Statistical Foundations Perceptrons and Logistic Regression Support Vector Machines