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Answer: Create a batch prediction job by using the actual sales data, and configure the job settings to generate feature attributions. Compare the results in the report.
The correct answer is B. Creating a batch prediction job using the actual sales data and configuring the job settings to generate feature attributions provides insights into how each feature in the data contributes to the model's predictions. This approach allows you to directly demonstrate how the model uses different features to make predictions, making it easier to explain the model's reasoning to stakeholders. Comparatively, simply comparing predictions to actuals (Option A) does not explain how the model arrives at those predictions. Generating counterfactual examples (Option C) can be useful for understanding model behavior but is not necessary for explaining the basic prediction process. Training another model (Option D) is unnecessary and time-consuming when feature attributions can provide the needed insights without additional model training.
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You are a data scientist at a retail company and have developed a Vertex AI forecast model to predict monthly item sales. The model was trained on historical sales data. Now, you want to create a report to explain how the model makes its predictions. You have access to one month of recent actual sales data that was not part of the training dataset. What is the best method to generate the necessary data for your report?
A
Create a batch prediction job by using the actual sales data. Compare the predictions to the actuals in the report.
B
Create a batch prediction job by using the actual sales data, and configure the job settings to generate feature attributions. Compare the results in the report.
C
Generate counterfactual examples by using the actual sales data. Create a batch prediction job using the actual sales data and the counterfactual examples. Compare the results in the report.
D
Train another model by using the same training dataset as the original, and exclude some columns. Using the actual sales data create one batch prediction job by using the new model and another one with the original model. Compare the two sets of predictions in the report.