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Get Batch Predictions

docs/rest/models/query-model-joined-with-data.mdx

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<Info> There are two ways to get batch predictions:
  1. Join the model with data tables and use the query endpoint to query for batch predictions.
  2. Query the model using this endpoint and provide data to be used by the model in the request. </Info>
<ResponseExample>
python
import requests
url = 'http://127.0.0.1:47334/api/projects/mindsdb/models/home_rentals_model/predict'

data = [{'number_of_rooms': 2,
  'number_of_bathrooms': 1,
  'sqft': 917,
  'location': 'great',
  'days_on_market': 13,
  'neighborhood': 'berkeley_hills',
  'rental_price': 3901,
  'created_at': '2024-02-24 02:28:21.746167'},
 {'number_of_rooms': 0,
  'number_of_bathrooms': 1,
  'sqft': 194,
  'location': 'great',
  'days_on_market': 10,
  'neighborhood': 'berkeley_hills',
  'rental_price': 2042,
  'created_at': '2024-02-19 06:10:59.693052'},
 {'number_of_rooms': 1,
  'number_of_bathrooms': 1,
  'sqft': 543,
  'location': 'poor',
  'days_on_market': 18,
  'neighborhood': 'westbrae',
  'rental_price': 1871,
  'created_at': '2024-02-12 07:53:45.914146'}]

r = requests.post(url, json={'data': data})
print(r.json())
json
[
    {
        "__mindsdb_row_id": null,
        "days_on_market": null,
        "location": null,
        "neighborhood": null,
        "number_of_bathrooms": null,
        "number_of_rooms": null,
        "rental_price": 2847,
        "rental_price_anomaly": null,
        "rental_price_confidence": 0.99,
        "rental_price_explain": "{\"predicted_value\": 2847, \"confidence\": 0.99, \"anomaly\": null, \"truth\": null, \"confidence_lower_bound\": 2730, \"confidence_upper_bound\": 2964}",
        "rental_price_max": 2964,
        "rental_price_min": 2730,
        "rental_price_original": null,
        "select_data_query": null,
        "sqft": 823,
        "when_data": null
    }
]
</ResponseExample> <Note>

The REST API endpoints can be used with MindsDB running locally at http://127.0.0.1:47334/api.

</Note>