eland.ml.MLModel

class eland.ml.MLModel(es_client: str | list[str] | tuple[str, ...] | Elasticsearch, model_id: str)

A machine learning model managed by Elasticsearch. (See https://www.elastic.co/guide/en/elasticsearch/reference/current/put-inference.html)

These models can be created by Elastic ML, or transformed from supported Python formats such as scikit-learn or xgboost and imported into Elasticsearch.

The methods for this class attempt to mirror standard Python classes.

__init__(es_client: str | list[str] | tuple[str, ...] | Elasticsearch, model_id: str)

Parameters

es_client: Elasticsearch client argument(s)

• elasticsearch-py parameters or

• elasticsearch-py instance

model_id: str

The unique identifier of the trained inference model in Elasticsearch.

Methods

__init__(es_client, model_id)	Parameters es_client: Elasticsearch client argument(s) elasticsearch-py parameters or elasticsearch-py instance
delete_model()	Delete an inference model saved in Elasticsearch
exists_model()	Check if the model already exists in Elasticsearch
import_ltr_model(es_client, model_id, model, ...)	Transform and serialize a trained 3rd party model into Elasticsearch.
import_model(es_client, model_id, model, ...)	Transform and serialize a trained 3rd party model into Elasticsearch.
predict(X)	Make a prediction using a trained model stored in Elasticsearch.

Attributes

feature_names
model_type
results_field