Commentary: a decomposition of the outlier detection problem into a set of supervised learning problems
作者:Ye Zhu, Kai Ming Ting
摘要
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).
论文关键词:Anomaly detection, Outlier detection, Isolation forest
论文评审过程:
论文官网地址:https://doi.org/10.1007/s10994-016-5566-8