Metadata-Version: 1.0
Name: iso_forest
Version: 1.0.3
Summary: Isolation Forest for anomaly detection
Home-page: https://github.com/mgckind/iso_forest
Author: Matias Carrasco Kind
Author-email: mcarras2@illinois.edu
License: License.txt
Description: # 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 iso_forest
        
        
        or directly from the Github repository
        
        
            pip install git+https://github.com/mgckind/iso_forest.git
         
        
        It supports python2 and python3 
        
        ## Requirements
        
        - numpy
        
        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
        
        - [basics](demo_iforest.ipynb)
        - [tree visualization and anomaly PDFs](demo_vis_pdf.ipynb)
        
        ## Releases 
        
        ### v1.0.3
        
        - Initial Release
        
        
Platform: UNKNOWN
