An anomaly detection package for data streams.
Project description
StreamAD
Anomaly detection for data streams/time series. Detectors process the univariate or multivariate data one by one to simulte a real-time scene.
Installation
The stable version can be installed from PyPI:
pip install streamad
The development version can be installed from GitHub:
pip install git+https://github.com/Fengrui-Liu/StreamAD
Quick Start
Start once detection within 5 lines of code. You can find more example with visualization results here.
from streamad.util import StreamGenerator, UnivariateDS
from streamad.model import SpotDetector
ds = UnivariateDS()
stream = StreamGenerator(ds.data)
model = SpotDetector()
for x in stream.iter_item():
score = model.fit_score(x)
Models
For univariate time series
If you want to detect multivarite time series with these models, you need to apply them on each feature separately.
For multivariate time series
These models are compatible with univariate time series.
Project details
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