Isolation Forest for anomaly detection
This is a simple package implementation for the isolation forest method described (among other places) in this [paper](icdm08b.pdf) for detecting anomalies and outliers from a data point distribution.
## Extended isolation forest
For an extended version of this algorithm that produces more precise scoring maps please visit this repository
pip install iso_forest
or directly from the Github repository
pip install git+https://github.com/mgckind/iso_forest.git
It supports python2 and python3
No extra requirements are needed for the algorithm.
In addition, it also contains means to draw the trees created using the [igraph](http://igraph.org/) library.
## Use Examples
See these 2 notebooks examples on how to use it
- [tree visualization and anomaly PDFs](demo_vis_pdf.ipynb)
- Initial Release
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