- Machine Learning: other versions:
- What is Elastic Machine Learning?
- Setup and security
- Anomaly detection
- Finding anomalies
- Tutorial: Getting started with anomaly detection
- Advanced concepts
- API quick reference
- How-tos
- Generating alerts for anomaly detection jobs
- Aggregating data for faster performance
- Altering data in your datafeed with runtime fields
- Customizing detectors with custom rules
- Detecting anomalous categories of data
- Reverting to a model snapshot
- Detecting anomalous locations in geographic data
- Mapping anomalies by location
- Adding custom URLs to machine learning results
- Anomaly detection jobs from visualizations
- Exporting and importing machine learning jobs
- Resources
- Data frame analytics
- Natural language processing
API quick reference
editAPI quick reference
editAll machine learning anomaly detection endpoints have the following base:
/_ml/
The main resources can be accessed with a variety of endpoints:
-
/anomaly_detectors/: Create and manage anomaly detection jobs -
/calendars/: Create and manage calendars and scheduled events -
/datafeeds/: Select data from Elasticsearch to be analyzed -
/filters/: Create and manage filters for custom rules -
/results/: Access the results of an anomaly detection job -
/model_snapshots/: Manage model snapshots
For a full list, see Machine learning anomaly detection APIs.
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