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:
Predicts the cluster for given data.
REQUIRED | KEY | TYPE | DESCRIPTION |
---|---|---|---|
Yes | deploymentToken | str | The deployment token used 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 | A unique string identifier for the deployment created under the project. |
Yes | queryData | dict | A dictionary where each 'key' represents a column name and its corresponding 'value' represents the value of that column. For Timeseries Clustering, the 'key' should be ITEM_ID, and its value should represent a unique item ID that needs clustering. |
KEY | TYPE | DESCRIPTION |
---|---|---|
success | Boolean | true if the call succeeded, false if there was an error |
Prediction |
TYPE | WHEN |
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DataNotFoundError |
|