Univariate outlier detection was the theme for Part II of the book; in this part, we will switch gears to multivariate outlier detection. Chapter 9 serves as the jumping-off point, as we cover the idea of clusters and see how clustering techniques can help us find outliers. We also wrap up univariate outlier detection by incorporating a univariate clustering technique into our existing ensemble. In Chapter 10, we introduce one of the multivariate clustering techniques we will use: Connectivity-Based Outlier Factor (COF). Chapter 11 brings us the other multivariate clustering technique: Local Correlation Integral (LOCI). Chapter 12 provides an important reminder that clustering techniques are not the only useful tools for multivariate analysis, as we review and implement Copula-Based Outlier Detection (COPOD).