2017-04-04 18:26:39 -04:00
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[[xpack-ml]]
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= Machine Learning in the Elastic Stack
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[partintro]
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--
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2017-05-02 15:45:42 -04:00
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The {xpackml} features automate the analysis of time-series data by creating
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2017-05-01 14:27:48 -04:00
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accurate baselines of normal behaviors in the data and identifying anomalous
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patterns in that data.
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Using proprietary {ml} algorithms, the following circumstances are detected,
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scored, and linked with statistically significant influencers in the data:
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* Anomalies related to temporal deviations in values, counts, or frequencies
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* Statistical rarity
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* Unusual behaviors for a member of a population
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Automated periodicity detection and quick adaptation to changing data ensure
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that you don’t need to specify algorithms, models, or other data science-related
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configurations in order to get the benefits of {ml}.
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[float]
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[[ml-intro]]
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== Integration with the Elastic Stack
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Machine learning is tightly integrated with the Elastic Stack. Data is pulled
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from {es} for analysis and anomaly results are displayed in {kib} dashboards.
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2017-04-04 18:26:39 -04:00
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--
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2017-05-05 13:40:17 -04:00
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include::overview.asciidoc[]
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2017-04-04 18:26:39 -04:00
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include::getting-started.asciidoc[]
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2017-05-19 16:40:50 -04:00
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include::configuring.asciidoc[]
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2017-11-14 21:04:21 -05:00
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include::stopping-ml.asciidoc[]
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2017-04-21 21:56:07 -04:00
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// include::ml-scenarios.asciidoc[]
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2017-04-04 18:26:39 -04:00
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include::api-quickref.asciidoc[]
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//include::troubleshooting.asciidoc[] Referenced from x-pack/docs/public/xpack-troubleshooting.asciidoc
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2017-06-05 16:07:15 -04:00
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include::functions.asciidoc[]
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