version 1.0.2

README.md

@@ -1,4 +1,4 @@
-<a href="https://github.com/sahandha/eif/releases/tag/v1.0.1"> <img src="https://img.shields.io/badge/release-v1.0.1-blue.svg" alt="latest release" /></a><a href="https://pypi.org/project/eif/1.0.1/"><img src="https://img.shields.io/badge/pypi-v1.0.1-orange.svg" alt="pypi version"/></a>
+<a href="https://github.com/sahandha/eif/releases/tag/v1.0.2"> <img src="https://img.shields.io/badge/release-v1.0.2-blue.svg" alt="latest release" /></a><a href="https://pypi.org/project/eif/1.0.2/"><img src="https://img.shields.io/badge/pypi-v1.0.2-orange.svg" alt="pypi version"/></a>
 # Extended Isolation Forest
 
 This is a simple package implementation for the Extended Isolation Forest method. It is an improvement on the original algorithm Isolation Forest which is described (among other places) in this [paper](icdm08b.pdf) for detecting anomalies and outliers from a data point distribution. The original code can be found at [https://github.com/mgckind/iso_forest](https://github.com/mgckind/iso_forest)
@@ -34,6 +34,10 @@ See these notebooks for examples on how to use it
 
 ## Release
 
+### v1.0.2
+#### 2018-OCT-01
+- Added documentation, examples and software paper
+
 ### v1.0.1
 #### 2018-AUG-08
 - Bugfix for multidimensional data

version.py

@@ -1,6 +1,6 @@
 """Extended isoforest version"""
 
-version_tag = (1, 0, 1)
+version_tag = (1, 0, 2)
 __version__ = '.'.join(map(str, version_tag[:3]))
 
 if len(version_tag) > 3: