Predict API

Once your model is trained, you must deploy the model on Abacus.AI platform to generate predictions. You can use the prediction dashboard to generate the predictions from the trained model. In this section the underlying prediction API and all other additional prediction API methods are discussed for the use case in consideration:

Method
getForecast POST
Copy POST

Returns a list of forecasts for a given entity under the specified project deployment. Note that the inputs to the deployed model will be the column names in your dataset mapped to the column mappings in our system (e.g. column 'holiday_yn' mapped to mapping 'FUTURE' in our system).

Arguments:

REQUIRED KEY TYPE DESCRIPTION
Yes deploymentToken str The deployment token to authenticate access to created deployments. This token is only authorized to predict on deployments in this project, so it is safe to embed this model inside of an application or website.
Yes deploymentId str The unique identifier to a deployment created under the project.
Yes queryData dict This will be a dictionary where 'Key' will be the column name (e.g. a column with name 'store_id' in your dataset) mapped to the column mapping ITEM_ID that uniquely identifies the entity against which forecasting is performed and 'Value' will be the unique value of the same entity.
No futureData List[dict] This will be a list of values known ahead of time that are relevant for forecasting (e.g. State Holidays, National Holidays, etc.). Each element is a dictionary, where the key and the value both will be of type 'str'. For example future data entered for a Store may be [{"Holiday":"No", "Promo":"Yes", "Date": "2015-07-31 00:00:00"}].
No numPredictions int The number of timestamps to predict in the future.
No predictionStart str The start date for predictions (e.g., "2015-08-01T00:00:00" as input for mid-night of 2015-08-01).
No explainPredictions bool Will explain predictions for forecasting
No explainerType str Type of explainer to use for explanations
No getItemData bool Will return the data corresponding to items in query
Note: The arguments for the API methods follow camelCase but for Python SDK underscore_case is followed.

Response:

KEY TYPE DESCRIPTION
success Boolean true if the call succeeded, false if there was an error
ForecastPrediction

Exceptions:

TYPE WHEN
DataNotFoundError

deploymentId is not found.

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