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Commentary: a decomposition of the outlier detection problem into a set of supervised learning problems

机译:评论:将异常值检测问题分解为一组有监督的学习问题

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This article discusses the material in relation to iForest (Liu et al. in ACM Trans Knowl Discov Data 6(1):3, 2012) reported in a recent Machine Learning Journal paper by Paulheim and Meusel (Mach Learn 100(2-3):509-531, 2015). It presents an empirical comparison result of iForest using the default parameter settings suggested by its creator (Liu et al. 2012) and iForest using the settings employed by Paulheim and Meusel (2015). This comparison has an impact on the conclusion made by Paulheim and Meusel (2015).
机译:本文讨论了Paulheim和Meusel在最近的《机器学习期刊》上发表的关于iForest的资料(Liu等人,在ACM Trans Knowl Discov Data 6(1):3,2012中)(Mach Learn 100(2-3)) :509-531,2015)。它使用创建者建议的默认参数设置(Liu等人,2012)和使用Paulheim和Meusel(2015)采用的设置建议的iForest,提供了iForest的经验比较结果。这种比较对Paulheim和Meusel(2015)得出的结论有影响。

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