Abstract
Ensemble analysis is a popular method used to improve the accuracy of various data mining algorithms. Ensemble methods combine the outputs of multiple algorithms or base detectors to create a unified output. The basic idea of the approach is that some algorithms will do well on a particular subset of points whereas other algorithms will do better on other subsets of points. However, the ensemble combination is often able to perform more robustly across the board because of its ability to combine the outputs of multiple algorithms. In this chapter, will use the terms base detector and component detector interchangeably to denote the individual algorithms whose outputs are combined to create the final result.
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Aggarwal, C.C. (2017). Outlier Ensembles. In: Outlier Analysis. Springer, Cham. https://doi.org/10.1007/978-3-319-47578-3_6
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DOI: https://doi.org/10.1007/978-3-319-47578-3_6
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