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
getAnomalies POST
Copy POST

Returns a list of anomalies from the training dataset.

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.
No threshold float The threshold score of what is an anomaly. Valid values are between 0.8 and 0.99.
No histogram bool If True, will return a histogram of the distribution of all points.
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
data JSON Object

Exceptions:

TYPE WHEN
DataNotFoundError

deploymentId is not found.

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