skchange
provides sktime
-compatible change detection and changepoint-based anomaly detection algorithms.
Experimental but maturing.
It is recommended to install skchange with numba
for faster performance:
pip install skchange[numba]
Alternatively, you can install skchange
without numba
:
pip install skchange
from skchange.change_detectors.moving_window import MovingWindow
from skchange.datasets.generate import generate_alternating_data
df = generate_alternating_data(n_segments=10, segment_length=50, mean=5, random_state=1)
detector = MovingWindow(bandwidth=10)
detector.fit_predict(df)
ilocs
0 50
1 100
2 150
3 200
4 250
5 300
6 350
7 400
8 450
import numpy as np
from skchange.anomaly_detectors import MVCAPA
from skchange.datasets.generate 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)
ilocs labels icolumns
0 [100, 120) 1 [0]
1 [250, 300) 2 [2, 1, 0]
skchange
is a free and open-source software licensed under the BSD 3-clause license.