Machine Learning

Machine learning is built into the Elastic Stack and enables users to gain insights into their Elasticsearch data. There are a wide range of capabilities from identifying in anomalies in your data, to training and deploying regression or classification models based on Elasticsearch data.

To use the Elastic Stack machine learning features, you must have the appropriate license and at least one machine learning node in your Elasticsearch cluster. If Elastic Stack security features are enabled, you must also ensure your users have the necessary privileges.

The fastest way to get started with machine learning features is to start a free 14-day trial of Elastic Cloud.

See Elasticsearch Machine Learning documentation more details.

MLModel

Constructor

MLModel(es_client, List[str], Tuple[str, …)

A machine learning model managed by Elasticsearch.

Predictions

MLModel.predict(X, List[float], …)

Make a prediction using a trained model stored in Elasticsearch.

Manage Models

MLModel.import_model(es_client, List[str], …)

Transform and serialize a trained 3rd party model into Elasticsearch.

MLModel.exists_model()

Check if the model already exists in Elasticsearch

MLModel.delete_model()

Delete an inference model saved in Elasticsearch