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| -rw-r--r-- | docs/category-overview-pages/machine-learning-and-assisted-troubleshooting.md | 8 |
1 files changed, 6 insertions, 2 deletions
diff --git a/docs/category-overview-pages/machine-learning-and-assisted-troubleshooting.md b/docs/category-overview-pages/machine-learning-and-assisted-troubleshooting.md index 074051e3e..f41089bba 100644 --- a/docs/category-overview-pages/machine-learning-and-assisted-troubleshooting.md +++ b/docs/category-overview-pages/machine-learning-and-assisted-troubleshooting.md @@ -1,3 +1,7 @@ -# Machine Learning and Assisted Troubleshooting Overview +# Machine Learning and Anomaly Detection -This section contains documentation regarding Netdata's troubleshooting and machine learning features.
\ No newline at end of file +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. |