firehol/netdata

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docs/category-overview-pages/machine-learning-and-assisted-troubleshooting.md

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# Machine Learning and Anomaly Detection

Netdata provides advanced Machine Learning features to help you identify and troubleshoot anomalies and unexpected behavior in your infrastructure before they become critical issues:

- K-means clustering [Machine Learning models](/src/ml/README.md) are trained to power the [Anomaly Advisor](/docs/dashboards-and-charts/anomaly-advisor-tab.md) on the dashboard, which allows you to identify Anomalies in your infrastructure.
- [Metric Correlations](/docs/metric-correlations.md) are possible through the dashboard using the [Two-sample Kolmogorov Smirnov](https://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test#Two-sample_Kolmogorov%E2%80%93Smirnov_test) statistical test and Volume heuristic measures.
- The [Netdata Assistant](/docs/netdata-assistant.md) is able to answer your prompts when it comes to troubleshooting Alerts and Anomalies.