Define Success Criteria for Test CERTIFIED-DATA-SCIENCE-PRACTITIONER Practice Questions (Page 2)

Questions 6–10

1. 6foundation · medium

   Which of the following is an example of a measurable success criterion for a binary classification model?

   • AThe model should achieve an F1-score of at least 0.85 on the held-out test set.
   • BThe model should be deployed to production within two weeks.
   • CThe model should be easy to interpret by business stakeholders.
   • DThe model should be fast enough for real-time predictions.
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2. 7expert · hard

   A data science team is working on a model for a client. The client has specified multiple success criteria, including a minimum accuracy of 0.90, a minimum recall of 0.80 for the positive class, and a maximum false positive rate of 0.10. The team has documented these criteria. During testing, the model achieves accuracy 0.92, recall 0.75, and false positive rate 0.08. What should the team do?

   • AAccept the model because it meets most of the criteria
   • BReport the model as successful because accuracy is above the threshold
   • CReject the model and retrain with a focus on improving recall
   • DAdjust the success criteria to match the model's performance
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4. 8foundation · medium

   Which evaluation metric is most appropriate for a regression problem?

   • AArea under the ROC curve (AUC)
   • BPrecision
   • CMean absolute error (MAE)
   • DF1-score
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5. 9application · medium

   A data science team is about to start testing a churn prediction model. The project manager wants to ensure that all stakeholders, including non-technical business leaders, understand what constitutes a successful model. Which action best supports this goal?

   • AKeep the success criteria confidential until the final model is selected
   • BUse only technical jargon to describe the criteria to avoid oversimplification
   • CDocument the success criteria in a shared document with clear definitions and examples
   • DDefine success criteria after the model is built to see what is achievable
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6. 10foundation · medium

   What is the purpose of setting a threshold for a success criterion, such as 'the model must achieve at least 0.80 AUC'?

   • ATo ensure the model is interpretable by stakeholders.
   • BTo increase the model's training speed.
   • CTo reduce the number of features used in the model.
   • DTo determine whether the model is acceptable for deployment.
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