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 list of anomalies from the training dataset.
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. |
KEY | TYPE | DESCRIPTION |
---|---|---|
success | Boolean | true if the call succeeded, false if there was an error |
data | JSON Object |
TYPE | WHEN |
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DataNotFoundError |
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