An Introduction to Outlier Ensembles.- Theory of Outlier Ensembles.- Variance Reduction in Outlier Ensembles.- Bias Reduction in Outlier Ensembles: The Guessing Game.- Model Combination Methods for Outlier Ensembles.- Which Outlier Detection Algorithm Should I Use?

This book discusses a variety of methods for outlier ensembles and organizes them by the specific principles with which accuracy improvements are achieved. In addition, it covers the techniques with which such methods can be made more effective. A formal classification of these methods is provided, and the circumstances in which they work well are examined. The authors cover how outlier ensembles relate (both theoretically and practically) to the ensemble techniques used commonly for other data mining problems like classification. The similarities and (subtle) differences in the ensemble techniques for the classification and outlier detection problems are explored. These subtle differences do impact the design of ensemble algorithms for the latter problem.