Chapter 10: Unsupervised Learning
Henry Schellhorn, Tianmin Kong · Society for Industrial and Applied Mathematics eBooks · 2024
Unsupervised learning has its roots in the classical problem of multivariate statistics: how to estimate a joint probability distribution , where denotes a vector-valued random variable in I dimensions. We will give a quick (and thus necessarily) incomplete summary of classical density estimation before turning to methods for higher dimensions, principal component analysis, and clustering.