Provides all the fundamental algorithms for outlier analysis in great detail including those for advanced data types, including specific insights into when and why particular algorithms work effectivelyDiscusses the latest ideas in the field such as outlier ensembles, matrix factorization, kernel methods, and neural networksCovers theoretical and practical aspects of outlier analysis including specific practical details for accurate implementationOffers numerous illustrations and exercises for classroom teaching, including a solution manual