This is a demo to show my implementation of isolation forest based on this paper
F. T. Liu, K. M. Ting and Z. Zhou, "Isolation Forest," 2008 Eighth IEEE International Conference on Data Mining, Pisa, 2008, pp. 413-422.
Isolation forests are used for anamoly detection and the idea is based on the observation that anomalies have distinctive quantitative properties:
- they are the minority consisting of fewer instances
- they have attribute-values that are very different from those of normal instances