Overview

Detecting anomalies in time series data can be enhanced by using additional external (or exogenous) features. Here, you’ll learn how to include exogenous variables in your anomaly detection workflow using Nixtla.

Key Benefits

  • Leverage additional context from exogenous features

  • Boost anomaly detection accuracy

  • Flexible usage via Azure AI or the public API

Including relevant exogenous variables can greatly improve anomaly detection, especially for time series influenced by external factors such as weather or market indicators.

For more detailed guidance on anomaly detection, including best practices and troubleshooting tips, see the

Anomaly Detection Guide

.

Continue exploring with the NixtlaClient methods for more advanced configurations and optimizations.