Merge pull request #187 from IFCA/fix_readme

Improve readme with additional info

Author: Jaime Céspedes Sisniega

README.md

@@ -17,6 +17,10 @@
   <a href="https://frouros.readthedocs.io/">
     <img src="https://readthedocs.org/projects/frouros/badge/?version=latest" alt="documentation"/>
   </a>
+  <!-- Downloads -->
+  <a href="https://pepy.tech/project/frouros">
+    <img src="https://static.pepy.tech/badge/frouros/month" alt="downloads"/>
+  </a>
   <!-- PyPI -->
   <a href="https://pypi.org/project/frouros">
     <img src="https://img.shields.io/pypi/v/frouros.svg?label=release&color=blue" alt="pypi">
@@ -187,9 +191,147 @@ pip install frouros
 
 ## 🕵🏻‍♂️️ Drift detection methods
 
-The currently implemented detectors are listed in the following diagram.
-
-![Detectors diagram](/images/detectors.png)
+The currently implemented detectors are listed in the following table.
+
+<table>
+<thead>
+  <tr>
+    <th>Drift detector</th>
+    <th>Type</th>
+    <th>Family</th>
+    <th>Method</th>
+    <th>Reference</th>
+  </tr>
+</thead>
+<tbody>
+  <tr>
+    <td rowspan="12">Concept drift</td>
+    <td rowspan="12">Streaming</td>
+    <td rowspan="3">CUMSUM</td>
+    <td>CUMSUM</td>
+    <td><a href="https://doi.org/10.2307/2333009">Page (1954)</a></td>
+  </tr>
+  <tr>
+    <td>Geometric moving average</td>
+    <td><a href="https://doi.org/10.2307/1266443">Roberts (1959)</a></td>
+  </tr>
+  <tr>
+    <td>Page Hinkley</td>
+    <td><a href="https://doi.org/10.2307/2333009">Page (1954)</a></td>
+  </tr>
+  <tr>
+    <td rowspan="6">Statistical process control</td>
+    <td>DDM</td>
+    <td><a href="https://doi.org/10.1007/978-3-540-28645-5_29">Gama et al. (2004)</a></td>
+  </tr>
+  <tr>
+    <td>ECDD-WT</td>
+    <td><a href="https://doi.org/10.1016/j.patrec.2011.08.019">Ross et al. (2012)</a></td>
+  </tr>
+  <tr>
+    <td>EDDM</td>
+    <td><a href="https://www.researchgate.net/publication/245999704_Early_Drift_Detection_Method">Baena-Garcıa et al. (2006)</a></td>
+  </tr>
+  <tr>
+    <td>HDDM-A</td>
+    <td><a href="https://doi.org/10.1109/TKDE.2014.2345382">Frias-Blanco et al. (2014)</a></td>
+  </tr>
+  <tr>
+    <td>HDDM-W</td>
+    <td><a href="https://doi.org/10.1109/TKDE.2014.2345382">Frias-Blanco et al. (2014)</a></td>
+  </tr>
+  <tr>
+    <td>RDDM</td>
+    <td><a href="https://doi.org/10.1016/j.eswa.2017.08.023">Barros et al. (2017)</a></td>
+  </tr>
+  <tr>
+    <td rowspan="3">Window based</td>
+    <td>ADWIN</td>
+    <td><a href="https://doi.org/10.1137/1.9781611972771.42">Bifet and Gavalda (2007)</a></td>
+  </tr>
+  <tr>
+    <td>KSWIN</td>
+    <td><a href="https://doi.org/10.1016/j.neucom.2019.11.111">Raab et al. (2020)</a></td>
+  </tr>
+  <tr>
+    <td>STEPD</td>
+    <td><a href="https://doi.org/10.1007/978-3-540-75488-6_27">Nishida and Yamauchi (2007)</a></td>
+  </tr>
+  <tr>
+    <td rowspan="14">Data drift</td>
+    <td rowspan="12">Batch</td>
+    <td rowspan="8">Distance based</td>
+    <td>Bhattacharyya distance</td>
+    <td><a href="https://www.jstor.org/stable/25047882">Bhattacharyya (1946)</a></td>
+  </tr>
+  <tr>
+    <td>Earth Mover's distance</td>
+    <td><a href="https://doi.org/10.1023/A:1026543900054">Rubner et al. (2000)</a></td>
+  </tr>
+  <tr>
+    <td>Hellinger distance</td>
+    <td><a href="https://doi.org/10.1515/CRLL.1909.136.210">Hellinger (1909)</a></td>
+  </tr>
+  <tr>
+    <td>Histogram intersection normalized complement</td>
+    <td><a href="https://doi.org/10.1007/BF00130487">Swain and Ballard (1991)</a></td>
+  </tr>
+  <tr>
+    <td>Jensen-Shannon distance</td>
+    <td><a href="https://doi.org/10.1109/18.61115">Lin (1991)</a></td>
+  </tr>
+  <tr>
+    <td>Kullback-Leibler divergence</td>
+    <td><a href="https://doi.org/10.1214/aoms/1177729694">Kullback and Leibler (1951)</a></td>
+  </tr>
+  <tr>
+    <td>MMD</td>
+    <td><a href="https://dl.acm.org/doi/10.5555/2188385.2188410">Gretton et al. (2012)</a></td>
+  </tr>
+  <tr>
+    <td>PSI</td>
+    <td><a href="https://doi.org/10.1057/jors.2008.144">Wu and Olson (2010)</a></td>
+  </tr>
+  <tr>
+    <td rowspan="4">Statistical test</td>
+    <td>Chi-square test</td>
+    <td><a href="https://doi.org/10.1080/14786440009463897">Pearson (1900)</a></td>
+  </tr>
+  <tr>
+    <td>Cramér-von Mises test</td>
+    <td><a href="https://doi.org/10.1080/03461238.1928.10416862">Cramér (1902)</a></td>
+  </tr>
+  <tr>
+    <td>Kolmogorov-Smirnov test</td>
+    <td><a href="https://doi.org/10.2307/2280095">Massey Jr (1951)</a></td>
+  </tr>
+  <tr>
+    <td>Welch's T-Test</td>
+    <td><a href="https://doi.org/10.2307/2332510">Welch (1947)</a></td>
+  </tr>
+  <tr>
+    <td rowspan="2">Streaming</td>
+    <td>Distance based</td>
+    <td>MMD</td>
+    <td><a href="https://dl.acm.org/doi/10.5555/2188385.2188410">Gretton et al. (2012)</a></td>
+  </tr>
+  <tr>
+    <td>Statistical test</td>
+    <td>Incremental Kolmogorov-Smirnov test</td>
+    <td><a href="https://doi.org/10.1145/2939672.2939836">dos Reis et al. (2016)</a></td>
+  </tr>
+</tbody>
+</table>
+
+## ✅ Who is using Frouros?
+
+Frouros is actively being used by the following projects to implement drift
+detection in machine learning pipelines:
+
+ * [AI4EOSC](https://ai4eosc.eu).
+ * [iMagine](https://imagine-ai.eu).
+
+If you want your project listed here, do not hesitate to send us a pull request.
 
 ## 👍 Contributing
 
@@ -210,4 +352,8 @@ Although Frouros paper is still in preprint, if you want to cite it you can use
 
 ## 📝 License
 
-Frouros is an open-source software licensed under the [BSD-3-Clause license](https://github.com/IFCA/frouros/blob/main/LICENSE).
+Frouros is an open-source software licensed under the [BSD-3-Clause license](https://github.com/IFCA/frouros/blob/main/LICENSE).
+
+## 🙏 Acknowledgements
+
+Frouros has received funding from the Agencia Estatal de Investigación, Unidad de Excelencia María de Maeztu, ref. MDM-2017-0765.