Anomaly Detection#

Anomaly Detection detects abnormal samples in a given time series. Chronos provides a set of unsupervised anomaly detectors.

View some examples notebooks for Datacenter AIOps.

1. ThresholdDetector#

ThresholdDetector detects anomaly based on threshold. It can be used to detect anomaly on a given time series (notebook), or used together with Forecasters to detect anomaly on new coming samples (notebook).

View ThresholdDetector API Doc for more details.

2. AEDetector#

AEDetector detects anomaly based on the reconstruction error of an autoencoder network.

View anomaly detection notebook and AEDetector API Doc for more details.

3. DBScanDetector#

DBScanDetector uses DBSCAN clustering algortihm for anomaly detection.


Users may install scikit-learn-intelex to accelerate this detector. Chronos will detect if scikit-learn-intelex is installed to decide if using it. More details please refer to:

View anomaly detection notebook and DBScanDetector API Doc for more details.