gecasmo 0.0.1

# gecasmo The gecasmo Python package, for estimating click models with covariates using EM.

## Installing `shell pip install gecasmo `

## Examples

The /notebooks directory contains a set of [Jupyter Notebook examples](https://github.com/cornederuijt/gecasmo/notebooks), including the following click models:

• [CZM](https://github.com/Mogeng/IOHMM/blob/master/examples/notebooks/UnSupervisedIOHMM.ipynb), also known as DBN [[1]](#1)

• [UBM](https://github.com/Mogeng/IOHMM/blob/master/examples/notebooks/SemiSupervisedIOHMM.ipynb) [[2]](#2)

## References <a id=”1”>[1]</a> Chapelle, Olivier, and Ya Zhang. (2009). A dynamic bayesian network click model for web search ranking. Proceedings of the 18th international conference on World wide web. ACM, 1–10.

<a id=”2”>[2]</a> Dupret, Georges E. and Piwowarski, Benjamin. (2008). A user browsing model to predict search engine click data from past observations. Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval. ACM, 331–338.

## Licensing The MIT Licence (MIT)