https://github.com/norskregnesentral/skchange

skchange provides sktime-compatible change detection and changepoint-based anomaly detection algorithms
https://github.com/norskregnesentral/skchange

anomaly-detection change-detection machine-learning statistics time-series-segmentation

Last synced: about 1 month ago
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skchange provides sktime-compatible change detection and changepoint-based anomaly detection algorithms

• Host: GitHub
• URL: https://github.com/norskregnesentral/skchange
• Owner: NorskRegnesentral
• License: bsd-3-clause
• Created: 2023-11-27T10:57:29.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-04-10T19:39:04.000Z (about 1 month ago)
• Last Synced: 2025-04-10T19:52:21.686Z (about 1 month ago)
• Topics: anomaly-detection, change-detection, machine-learning, statistics, time-series-segmentation
• Language: Python
• Homepage: https://skchange.readthedocs.io
• Size: 4.6 MB
• Stars: 27
• Watchers: 4
• Forks: 4
• Open Issues: 8
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# skchange

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[![docs](https://readthedocs.org/projects/skchange/badge/?version=latest)](https://skchange.readthedocs.io/en/latest/?badge=latest)

[![BSD 3-clause](https://img.shields.io/badge/License-BSD%203--Clause-blue.svg)](https://github.com/sktime/sktime/blob/main/LICENSE)

[![!black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

[![Python](https://img.shields.io/pypi/pyversions/skchange)](https://pypi.org/project/skchange/)

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[skchange]((https://skchange.readthedocs.io/en/latest/)) provides [sktime](https://www.sktime.net/)-compatible change detection and changepoint-based anomaly detection algorithms.

Experimental but maturing.

Check out the latest version: [v0.12.0](https://github.com/NorskRegnesentral/skchange/releases)

## Documentation

* [Documentation](https://skchange.readthedocs.io/)

* [Notebook tutorial](https://github.com/sktime/sktime-tutorial-pydata-global-2024)

## Installation

It is recommended to install skchange with [numba](https://numba.readthedocs.io/en/stable/) for faster performance:

```sh

pip install skchange[numba]

```

Alternatively, you can install skchange without numba:

```sh

pip install skchange

```

## Quickstart

### Changepoint detection / time series segmentation

```python

from skchange.change_detectors import MovingWindow

from skchange.datasets import generate_alternating_data

df = generate_alternating_data(n_segments=10, segment_length=50, mean=5, random_state=1)

detector = MovingWindow(bandwidth=20)

detector.fit_predict(df)

```

```python

   ilocs

0     50

1    100

2    150

3    200

4    250

5    300

6    350

7    400

8    450

```

### Multivariate anomaly detection

```python

import numpy as np

from skchange.anomaly_detectors import MVCAPA

from skchange.datasets import generate_anomalous_data

n = 300

anomalies = [(100, 120), (250, 300)]

means = [[8.0, 0.0, 0.0], [2.0, 3.0, 5.0]]

df = generate_anomalous_data(n, anomalies, means, random_state=3)

detector = MVCAPA()

detector.fit_predict(df)

```

```python

        ilocs  labels   icolumns

0  [100, 120)       1        [0]

1  [250, 300)       2  [2, 1, 0]

```

## License

skchange is a free and open-source software licensed under the [BSD 3-clause license](https://github.com/NorskRegnesentral/skchange/blob/main/LICENSE).