Welcome to the documentation of dtaianomaly!

dtaianomaly is an easy-to-use Python package for time series anomaly detection. Its main goal is to offer a simple interface to detect anomalies in time series data using state-of-the-art methods. Additionally, dtaianomaly provides a benchmark framework to quantitatively evaluate time series anomaly detection methods on a large repository of time series.

The source is available on GitHub.

Getting started

• Installation
• Anomaly detection
• Custom models
• Quantitative evaluation with a workflow
• Time series anomaly detection benchmarks

Documentation

• Anomaly detection module
• Data module
• Preprocessing module
• Thresholding module
• Evaluation module
• Pipeline module
• Workflow module
• Visualization module