Metadata-Version: 2.1
Name: ChannelAttribution
Version: 2.0.2
Summary: Markov Model for Online Multi-Channel Attribution
Home-page: http://www.channelattribution.net
Author: Davide Altomare, David Loris
Author-email: info@channelattribution.net
License: GPLv3
Project-URL: Documentation, http://www.channelattribution.net
Project-URL: Code, https://github.com/DavideAltomare/ChannelAttribution
Project-URL: Issue tracker, https://github.com/DavideAltomare/ChannelAttribution/issues
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: C++
Classifier: Programming Language :: Cython
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: Implementation :: CPython
Requires-Python: >=3.4
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: pandas

Python library *ChannelAttribution*
===================================

Advertisers use a variety of online marketing channels to reach consumers and they want to know the degree each channel contributes to their marketing success. This is called online multi-channel attribution problem. ChannelAttribution implements a probabilistic algorithm for the attribution problem. The model uses a k-order Markov representation to identify structural correlations in the customer journey data.

Installation
------------

### From PyPi

```bash
pip install --upgrade setuptools
pip install ChannelAttribution
```

### Generating documentation

```bash
cd ...\src\cypack

python generate_doc.py
```

The following .pdf will be generated:

.../src/cypack/docs/_build/rinoh/channelattribution.pdf


