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:
Returns a prediction for Predictive Modeling
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. |
KEY | TYPE | DESCRIPTION |
---|---|---|
success | Boolean | true if the call succeeded, false if there was an error |
Prediction |
TYPE | WHEN |
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DataNotFoundError |
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