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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"
}