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: 5 days 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 (12 months ago)
• Default Branch: main
• Last Pushed: 2024-10-22T12:55:44.000Z (15 days ago)
• Last Synced: 2024-10-23T08:59:17.296Z (14 days ago)
• Topics: anomaly-detection, change-detection, machine-learning, statistics, time-series-segmentation
• Language: Python
• Homepage: https://skchange.readthedocs.io
• Size: 470 KB
• Stars: 8
• Watchers: 4
• Forks: 2
• Open Issues: 7
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# [skchange](https://skchange.readthedocs.io/en/latest/)

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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)

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`skchange` provides sktime-compatible change detection and changepoint-based anomaly detection algorithms.

Experimental but maturing.

## [Documentation](https://skchange.readthedocs.io/en/latest/)

Now available.

## Installation

```sh

pip install skchange

```

Requires Python >= 3.9, < 3.13.

## Quickstart

### Changepoint detection / time series segmentation

```python

from skchange.change_detectors.moscore import Moscore

from skchange.datasets.generate import generate_alternating_data

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

detector = Moscore(bandwidth=10)

detector.fit_predict(df)

```

```python

0     49

1     99

2    149

3    199

4    249

5    299

6    349

7    399

8    449

Name: changepoint, dtype: int64

```

### Multivariate anomaly detection

```python

import numpy as np

from skchange.anomaly_detectors import Mvcapa

from skchange.datasets.generate import generate_anomalous_data

n = 300

anomalies = [(100, 119), (250, 299)]

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

  anomaly_interval anomaly_columns

0       [100, 119]             [0]

1       [250, 299]       [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).