Create model
Create a forecast model.
Creates a new forecast model. You must provide a name and a location (via a Saved Location ID). Optionally specify demand_type, label, external_id, forecast_window, algo, and generate_baseline.
After creating a model, upload historical demand data using the Create Demand Data endpoint, then trigger training.
Enter your PredictHQ API key. The Bearer prefix is added automatically.
When calling the API directly, send: Authorization: Bearer <YOUR_API_KEY> as documented at https://docs.predicthq.com/api/overview/authenticating
Name for the forecast model.
External identifier for the forecast model. If you have an ID for the location/store/property/product-group in your other platforms, use the same ID here to easily connect this specific forecast model.
Number of days into the future to forecast.
When true, generates a baseline model using historical demand data only - without PredictHQ demand intelligence - for benchmarking accuracy against the enhanced model.
falseSet of labels you can use to better identify or group your forecast models.
Currently we offer one algorithm based on XGBoost. In the future we may offer additional algos.
phq-xgboostSuccessful Response
List of error messages, if any.
[]List of warning messages, if any.
[]Unique identifier for the newly created forecast model.
Bad Request
Unauthorized
Payment Required
Forbidden
POST /v1/forecasts/models HTTP/1.1
Host: api.predicthq.com
Authorization: Bearer YOUR_SECRET_TOKEN
Content-Type: application/json
Accept: */*
Content-Length: 224
{
"name": "text",
"external_id": "text",
"forecast_window": "1d",
"generate_baseline": false,
"label": [
"text"
],
"location": {
"saved_location_id": "text"
},
"algo": "phq-xgboost",
"demand_type": {
"interval": "text",
"industry": "accommodation"
}
}{
"errors": [
"text"
],
"warnings": [
"text"
],
"model_id": "text"
}OpenAPI Spec
The OpenAPI spec for Forecasts API can be found here.
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