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Overview

This node integrates with the Dataiku DSS API, enabling users to perform a wide range of operations on Dataiku DSS resources directly from n8n workflows. Specifically, for the Machine Learning - Lab resource and the Compute Subpopulation Analysis of Trained Model operation, the node launches the computation of subpopulation analyses for a trained machine learning model within a specified project and analysis context.

This functionality is beneficial when you want to analyze how different subpopulations (segments) behave or perform under a trained model, which can help in understanding model fairness, bias, or performance variations across groups.

Practical example:
You have a trained model deployed in Dataiku DSS and want to compute subpopulation analyses to evaluate its behavior on various customer segments (e.g., age groups, regions). Using this node, you can trigger the computation of these analyses programmatically as part of an automated workflow.

Properties

Name Meaning
Project Key The unique identifier of the Dataiku DSS project where the model and analysis reside.
Analysis ID The identifier of the specific analysis within the project related to the ML task.
ML Task ID The identifier of the machine learning task associated with the trained model.
Model Full ID The full identifier of the trained model for which the subpopulation analysis will be computed.
Request Body A JSON object containing additional parameters or configuration for the API request.

Output

  • The output is returned as JSON data representing the response from the Dataiku DSS API after launching the subpopulation analysis computation.
  • The structure typically includes details about the initiated computation task or confirmation of the action.
  • If the operation involves downloading files or binary content (not applicable specifically here), the node would return binary data prepared for further use.

Dependencies

  • Requires valid Dataiku DSS API credentials, including:
    • The URL of the Dataiku DSS server.
    • An API key for authentication.
  • The node uses HTTP requests to communicate with the Dataiku DSS REST API.
  • No additional external dependencies beyond the configured credentials and network access to the Dataiku DSS instance.

Troubleshooting

  • Missing Credentials Error:
    If the node throws an error about missing credentials, ensure that the Dataiku DSS API credentials are properly configured in n8n.

  • Required Parameter Missing:
    Errors like "Project Key is required" or "Analysis ID is required" indicate that mandatory input properties were not provided. Verify all required fields are set.

  • API Request Failures:
    Network issues, incorrect URLs, or insufficient permissions may cause API call failures. Check connectivity to the Dataiku DSS server and user permissions.

  • Invalid JSON in Request Body:
    If using the Request Body property, ensure the JSON is well-formed to avoid parsing errors.

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