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A Python library for online changepoint detection, implementing well-known and recent algorithms.

Project description

ocpdet

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

DOI

A Python package for online changepoint detection in univariate and multivariate data.

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's 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 v0.0.1). Zenodo. https://doi.org/10.5281/zenodo.7232039

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      = {v0.0.1},
  doi          = {10.5281/zenodo.7232039},
  url          = {https://doi.org/10.5281/zenodo.7232039}
}

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 MIT license.

Project details


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Source Distribution

ocpdet-0.0.1.tar.gz (8.7 kB view hashes)

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