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"
}