You're viewing version 2.13 of the OpenSearch documentation. This version is no longer maintained. For the latest version, see the current documentation. For information about OpenSearch version maintenance, see Release Schedule and Maintenance Policy.
Train
The train API operation trains a model based on a selected algorithm. Training can occur both synchronously and asynchronously.
Example request
The following examples use the k-means algorithm to train index data.
Train with k-means synchronously
POST /_plugins/_ml/_train/kmeans
{
"parameters": {
"centroids": 3,
"iterations": 10,
"distance_type": "COSINE"
},
"input_query": {
"_source": ["petal_length_in_cm", "petal_width_in_cm"],
"size": 10000
},
"input_index": [
"iris_data"
]
}
Train with k-means asynchronously
POST /_plugins/_ml/_train/kmeans?async=true
{
"parameters": {
"centroids": 3,
"iterations": 10,
"distance_type": "COSINE"
},
"input_query": {
"_source": ["petal_length_in_cm", "petal_width_in_cm"],
"size": 10000
},
"input_index": [
"iris_data"
]
}
Example response
Synchronous
For synchronous responses, the API returns the model_id, which can be used to get or delete a model.
{
"model_id" : "lblVmX8BO5w8y8RaYYvN",
"status" : "COMPLETED"
}
Asynchronous
For asynchronous responses, the API returns the task_id, which can be used to get or delete a task.
{
"task_id" : "lrlamX8BO5w8y8Ra2otd",
"status" : "CREATED"
}