- 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
editAPI 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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