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POST
/
api
/
models
/
train
Train Model
curl --request POST \
  --url https://api.example.com/api/models/train \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model_name": "<string>",
  "model_type": "prediction",
  "model_description": "<string>",
  "dataset_version_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "dataset_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "label_column": "<string>",
  "input_columns": [
    "<string>"
  ],
  "params": {},
  "idempotency_key": "<string>"
}
'
{
  "model_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "model_version_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "job_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "status": "<string>",
  "ml_runtime_version": "<string>"
}

Authorizations

​
Authorization
string
header
required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Headers

​
X-API-Key
string | null

Body

application/json

Request to train a model.

​
model_name
string
required
​
model_type
enum<string>
required

Canonical model types supported by the ML layer.

Available options:
prediction,
anomaly,
embedding,
clustering,
factors
​
model_description
string | null
​
dataset_version_id
string<uuid> | null
​
dataset_id
string<uuid> | null
​
label_column
string | null
​
input_columns
string[] | null
​
params
Params · object
​
idempotency_key
string | null

Response

Successful Response

Response for training a model.

​
model_id
string<uuid>
required
​
model_version_id
string<uuid>
required
​
job_id
string<uuid>
required
​
status
string
required
​
ml_runtime_version
string
required