AIF-C01 · Question #73
A company makes forecasts each quarter to decide how to optimize operations to meet expected demand. The company uses ML models to make these forecasts. An AI practitioner is writing a report about…
The correct answer is B. Partial dependence plots (PDPs). Partial dependence plots (PDPs) are visual tools used to show the relationship between a feature (or a set of features) in the data and the predicted outcome of a machine learning model. They are highly effective for providing transparency and explainability of the model's…
Question
A company makes forecasts each quarter to decide how to optimize operations to meet expected demand. The company uses ML models to make these forecasts. An AI practitioner is writing a report about the trained ML models to provide transparency and explainability to company stakeholders. What should the AI practitioner include in the report to meet the transparency and explainability requirements?
Options
- ACode for model training
- BPartial dependence plots (PDPs)
- CSample data for training
- DModel convergence tables
How the community answered
(39 responses)- A5% (2)
- B69% (27)
- C10% (4)
- D15% (6)
Explanation
Partial dependence plots (PDPs) are visual tools used to show the relationship between a feature (or a set of features) in the data and the predicted outcome of a machine learning model. They are highly effective for providing transparency and explainability of the model's behavior to stakeholders by illustrating how different input variables impact the model's predictions.
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