[[xpack-ml]]
= Machine Learning in the Elastic Stack

[partintro]
--
The {xpackml} features automate the analysis of time-series data by creating
accurate baselines of normal behaviors in the data and identifying anomalous
patterns in that data.

Using proprietary {ml} algorithms, the following circumstances are detected,
scored, and linked with statistically significant influencers in the data:

* Anomalies related to temporal deviations in values, counts, or frequencies
* Statistical rarity
* Unusual behaviors for a member of a population

Automated periodicity detection and quick adaptation to changing data ensure
that you don’t need to specify algorithms, models, or other data science-related
configurations in order to get the benefits of {ml}.

[float]
[[ml-intro]]
== Integration with the Elastic Stack

Machine learning is tightly integrated with the Elastic Stack. Data is pulled
from {es} for analysis and anomaly results are displayed in {kib} dashboards.

--

include::overview.asciidoc[]
include::getting-started.asciidoc[]
include::configuring.asciidoc[]
// include::ml-scenarios.asciidoc[]
include::api-quickref.asciidoc[]
//include::troubleshooting.asciidoc[]  Referenced from x-pack/docs/public/xpack-troubleshooting.asciidoc