# iso_forest
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
[https://github.com/sahandha/eif](https://github.com/sahandha/eif)/
## Installation
pip install git+https://github.com/mgckind/iso_forest.git
It supports python2 and python3
## Requirements
No extra requirements are needed, 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
[basics](demo_iforest.ipynb)
[tree visualization and anomaly PDFs](demo_vis_pdf.ipynb)
## Releases
### v1.0.1
Initial Release
1 maintainer
Metadata
1 maintainer
Release files for iso-forest 1.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| iso_forest-1.0.2.tar.gz | 3.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| iso_forest-1.0.2-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 8.0 kB
Release files / iso_forest-1.0.2.tar.gz
| Download URL | iso_forest-1.0.2.tar.gz |
|---|---|
| Size | 3.2 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / iso_forest-1.0.2-py2.py3-none-any.whl
| Download URL | iso_forest-1.0.2-py2.py3-none-any.whl |
|---|---|
| Size | 4.8 kB |
| Tags | Python 2 Python 3 |
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SHA-256 checksum How to use checksums |
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