Data Mining: Concepts and Techniques, 3rd Edition

Publisher Summary

This chapter aims to study outlier detection techniques. The different types of outliers are defined. An overview of outlier detection methods is also presented. Assume that a given statistical process is used to generate a set of data objects. An outlier is a data object that deviates significantly from the rest of the objects, as if it were generated by a different mechanism. Types of outliers include global outliers, contextual outliers, and collective outliers. An object may be more than one type of outlier. Outlier detection (also known as anomaly detection) is the process of finding data objects with behaviors that are very different from expectation. Outlier detection is important in many applications in addition to fraud ...