- Machine Learning: other versions:
- Setup and security
- Getting started with machine learning
- Anomaly detection
- Overview
- Concepts
- Configure anomaly detection
- API quick reference
- Supplied configurations
- Function reference
- Examples
- Generating alerts for anomaly detection jobs
- Aggregating data for faster performance
- Customizing detectors with custom rules
- Detecting anomalous categories of data
- Detecting anomalous locations in geographic data
- Performing population analysis
- Altering data in your datafeed with runtime fields
- Adding custom URLs to machine learning results
- Handling delayed data
- Mapping anomalies by location
- Limitations
- Troubleshooting
- Data frame analytics
IMPORTANT: No additional bug fixes or documentation updates
will be released for this version. For the latest information, see the
current release documentation.
API quick reference
edit
IMPORTANT: This documentation is no longer updated. Refer to Elastic's version policy and the latest documentation.
API quick reference
editAll data frame analytics endpoints have the following base:
/_ml/data_frame/analytics
The evaluation API endpoint has the following base:
/_ml/data_frame/_evaluate
All the trained models endpoints have the following base:
/_ml/trained_models/
- Create data frame analytics jobs
- Create trained model aliases
- Create trained models
- Delete data frame analytics jobs
- Delete trained models
- Evaluate data frame analytics
- Explain data frame analytics
- Get data frame analytics jobs info
- Get data frame analytics jobs statistics
- Get trained models
- Get trained models statistics
- Preview data frame analytics
- Start data frame analytics jobs
- Stop data frame analytics jobs
- Update data frame analytics jobs
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