Isolation Mondrian Forest (iMondrian Forest)

The code for Isolation Mondrian (iMondrian) forest for batch and online anomaly detection

iMondrian Forest (Ours)

This is the code for the paper:

Haoran Ma, Benyamin Ghojogh, Maria N. Samad, Dongyu Zheng, Mark Crowley. "Isolation Mondrian Forest for Batch and Online Anomaly Detection." In 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 3051-3058. IEEE, 2020.

• Link to paper: https://ieeexplore.ieee.org/abstract/document/9283073

• Link to arXiv version: https://arxiv.org/abs/2003.03692

iMondrian forest is a hybrid of isolation forest (for batch anomaly detection) and Mondrian forest (for online classification and regression). iMondrian forest can be used for both batch and online anomaly detection.

Isolation Forest

Fei Tony Liu, Kai Ming Ting, Zhi-Hua Zhou. "Isolation forest." In 2008 eighth ieee international conference on data mining, pp. 413-422. IEEE, 2008.

• Link to paper: https://ieeexplore.ieee.org/abstract/document/4781136

Fei Tony Liu, Kai Ming Ting, Zhi-Hua Zhou. "Isolation-based anomaly detection." ACM Transactions on Knowledge Discovery from Data (TKDD) 6, no. 1 (2012): 1-39.

• Link to paper: https://dl.acm.org/doi/abs/10.1145/2133360.2133363

• Link to isolation forest code library: https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.IsolationForest.html

Mondrian Forest

Balaji Lakshminarayanan, Daniel M. Roy, Yee Whye Teh. "Mondrian forests: Efficient online random forests." Advances in Neural Information Processing Systems 27 (NIPS), pages 3140-3148, 2014.

• Link to paper: https://papers.nips.cc/paper/2014/hash/d1dc3a8270a6f9394f88847d7f0050cf-Abstract.html

• Link to Mondrian forest codes:

  • https://scikit-garden.github.io/examples/MondrianTreeRegressor/
  • https://github.com/nel215/mondrianforest
  • https://github.com/balajiln/mondrianforest