Published April 3, 2024
| Version
0.1.0
Python Library
Open
Anomaly Diagnostic based on Counterfactual Analysis
Owner
Description
This module performs anomalous segments detection in univariate time series, leveraging their structural similarities.
A multiscale representation of the signal is derived to enable the detection of anomalous segments of unprescribed lengths.
As an important by-product, a pattern-based time series dissimilarity metric is provided.
Files
Files
(17.1 kB)
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|---|---|---|
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md5:3199afd6df43ad51f4c587ebb3027778
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17.1 kB | Download |
Additional details
- Functional maturity
- Technological maturity
Trustworthy Attributes
Reliability
Engineering roles
Data Engineer
Use cases
Time series
Functional Set
Data Life cycle