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Titlebook: Outlier Ensembles; An Introduction Charu C. Aggarwal,Saket Sathe Textbook 2017 Springer International Publishing AG 2017 Data mining.Outlie

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發(fā)表于 2025-3-23 11:22:16 | 只看該作者
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發(fā)表于 2025-3-23 13:58:25 | 只看該作者
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發(fā)表于 2025-3-23 22:01:42 | 只看該作者
https://doi.org/10.1007/978-3-319-54765-7Data mining; Outlier ensembles; Ensemble analysis; Bagging; Classification; Heterogeneous model combinati
14#
發(fā)表于 2025-3-24 00:57:02 | 只看該作者
Charu C. Aggarwal,Saket SatheProvides a comprehensive overview of the field including the theory of outlier ensembles and various techniques built around this theory.Offers numerous practical insights about the implementation of
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發(fā)表于 2025-3-24 04:46:52 | 只看該作者
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發(fā)表于 2025-3-24 21:27:24 | 只看該作者
Model Combination Methods for Outlier Ensembles,bination methods. For example, the impact of the scheme of averaging is quite different from that of maximization in terms of the bias and variance of the result. Therefore, the choice of model combination has a crucial effect on the results of the ensemble.
20#
發(fā)表于 2025-3-25 01:56:49 | 只看該作者
Which Outlier Detection Algorithm Should I Use?,ity. What is the impact of using generic ensemble methods on various base detectors? What is the impact of combining these ensemble methods into a higher-level combination? This chapter will discuss both these different ways of combining base detectors and also various ways in which one can squeeze the most out of ensemble methods.
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