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
predict POST
Copy POST

Returns a prediction for Predictive Modeling

Arguments:

REQUIRED KEY TYPE DESCRIPTION
Yes deploymentToken str A deployment token used to authenticate access to created deployments. This token is only authorized to predict on deployments in this project, and is safe to embed in an application or website.
Yes deploymentId str A unique identifier for a deployment created under the project.
Yes queryData dict A dictionary where the key is the column name (e.g. a column with name 'user_id' in the dataset) mapped to the column mapping USER_ID that uniquely identifies the entity against which a prediction is performed, and the value is the unique value of the same entity.
No kwargs dict Additional usecase specific keyword arguments to be passed. Example - explain_predictions for regression models.
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
Prediction

Exceptions:

TYPE WHEN
DataNotFoundError

deploymentId is not found.

Language: