tsadmetrics 0.1.17

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TSADmetrics - Time Series Anomaly Detection Metrics

TSADmetrics is a Python library for evaluating anomaly detection algorithms in time series data. It provides a comprehensive set of binary and non-binary metrics designed specifically for the challenges of anomaly detection in temporal contexts.

Features

• Binary Metrics: Evaluate discrete anomaly predictions (0/1 labels)

• Non-Binary Metrics: Assess continuous anomaly scores

• Efficient Computation: Compute multiple metrics at once

• CLI Tool: Evaluate metrics directly from CSV/JSON files

Installation

Install TSADmetrics via pip:

pip install tsadmetrics

Documentation

The complete documentation for TSADmetrics is available at:
���� https://tsadmetrics.readthedocs.io/

Acknowledgements

This library is based on the concepts and implementations from:
S��rb��, S., & Ruocco, M. (2023). Navigating the metric maze: a taxonomy of evaluation metrics for anomaly detection in time series. https://doi.org/10.1007/s10618-023-00988-8