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

  1. POST /_plugins/_ml/_train/kmeans
  2. {
  3.     "parameters": {
  4.         "centroids": 3,
  5.         "iterations": 10,
  6.         "distance_type": "COSINE"
  7.     },
  8.     "input_query": {
  9.         "_source": ["petal_length_in_cm", "petal_width_in_cm"],
  10.         "size": 10000
  11.     },
  12.     "input_index": [
  13.         "iris_data"
  14.     ]
  15. }

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Train with k-means asynchronously

  1. POST /_plugins/_ml/_train/kmeans?async=true
  2. {
  3.     "parameters": {
  4.         "centroids": 3,
  5.         "iterations": 10,
  6.         "distance_type": "COSINE"
  7.     },
  8.     "input_query": {
  9.         "_source": ["petal_length_in_cm", "petal_width_in_cm"],
  10.         "size": 10000
  11.     },
  12.     "input_index": [
  13.         "iris_data"
  14.     ]
  15. }

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Example response

Synchronous

For synchronous responses, the API returns the model_id, which can be used to get or delete a model.

  1. {
  2.   "model_id" : "lblVmX8BO5w8y8RaYYvN",
  3.   "status" : "COMPLETED"
  4. }

Asynchronous

For asynchronous responses, the API returns the task_id, which can be used to get or delete a task.

  1. {
  2.   "task_id" : "lrlamX8BO5w8y8Ra2otd",
  3.   "status" : "CREATED"
  4. }