ocpdet

A Python package for online changepoint detection, implementing state-of-the-art algorithms and a novel approach.


Keywords
changepoint-detection, deep-learning, package
License
BSD-3-Clause
Install
pip install ocpdet==0.0.6

Documentation

ocpdet

OCPDet is an open-source Python package for online changepoint detection, implementing state-of-the-art algorithms and a novel approach, using a scikit-learn style API.

PyPI DOI

This package is the outcome of my Master Thesis at Imperial College London within the MSc in Statistics, Department of Mathematics.

Algorithms implemented in ocpdet are

  • CUSUM: Cumulative Sum algorithm, proposed by Page (1954)
  • EWMA: Exponentially Weighted Moving Average algorithm, proposed by Roberts (1959)
  • Two Sample tests: Nonparametric hypothesis testing for changepoint detection, proposed by Ross et al. (2011)
  • Neural Networks: Novel approach based on sequentially learning neural networks, proposed by Hushchyn et al. (2020) and extended to online context (Master Thesis)

Installation

pip install ocpdet

Examples

How to cite this work

Here is a suggestion to cite this GitHub repository:

Victor Khamesi. (2022). ocpdet: A Python package for online changepoint detection in univariate and multivariate data. (Version v0.0.5). Zenodo. https://doi.org/10.5281/zenodo.7632721

And a possible BibTeX entry:

@software{victor_khamesi_2022,
  author       = {Victor Khamesi},
  title        = {ocpdet: A Python package for online changepoint detection in univariate and multivariate data.},
  month        = oct,
  year         = 2022,
  publisher    = {Zenodo},
  version      = {v0.0.5},
  doi          = {10.5281/zenodo.7632721},
  url          = {https://doi.org/10.5281/zenodo.7632721}
}

License

The non-software content of this project is licensed under a Creative Commons Attribution 4.0 International License, and the software code is licensed under the BSD-2 Clause license.