Outlier detection using isolation forest and local outlier factor-Reference-Cited by-同舟云学术

Outlier detection using isolation forest and local outlier factor

Published:2019-09-24 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Conference on Research in Adaptive and Convergent Systems
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Author:

Cheng Zhangyu¹,Zou Chengming¹,Dong Jianwei²

Affiliation:

1. Wuhan University of Technology, Wuhan, China

2. People's Hospital of Ningxia Hui Autonomous Region, Ningxia, China

Funder

National Key R&D Program of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3338840.3355641

Reference19 articles.

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2. LOF

3. Softening Splits in Decision Trees Using Simulated Annealing

4. Sarah Erfani Mahsa Baktashmotlagh Sutharshan Rajasegarar Shanika Karunasekera and Chris Leckie. 2015. R1SVM: A randomised nonlinear approach to large-scale anomaly detection. (2015). Sarah Erfani Mahsa Baktashmotlagh Sutharshan Rajasegarar Shanika Karunasekera and Chris Leckie. 2015. R1SVM: A randomised nonlinear approach to large-scale anomaly detection. (2015).

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