Commentary: A Decomposition of the Outlier Detection Problem into a Set of Supervised Learning Problems
Abstract
This article discusses the material in relation to i Forest (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 i Forest using the default parameter settings suggested by its creator (Liu et al. 2012 ) and i Forest using the settings employed by Paulheim and Meusel ( 2015 ). This comparison has an impact on the conclusion made by Paulheim and Meusel ( 2015 ).
Cite
Text
Zhu and Ting. "Commentary: A Decomposition of the Outlier Detection Problem into a Set of Supervised Learning Problems." Machine Learning, 2016. doi:10.1007/S10994-016-5566-8Markdown
[Zhu and Ting. "Commentary: A Decomposition of the Outlier Detection Problem into a Set of Supervised Learning Problems." Machine Learning, 2016.](https://mlanthology.org/mlj/2016/zhu2016mlj-commentary/) doi:10.1007/S10994-016-5566-8BibTeX
@article{zhu2016mlj-commentary,
title = {{Commentary: A Decomposition of the Outlier Detection Problem into a Set of Supervised Learning Problems}},
author = {Zhu, Ye and Ting, Kai Ming},
journal = {Machine Learning},
year = {2016},
pages = {301-304},
doi = {10.1007/S10994-016-5566-8},
volume = {105},
url = {https://mlanthology.org/mlj/2016/zhu2016mlj-commentary/}
}