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AI Associate Salesforce Einstein AI Features Practice Question

A company wants to build a custom AI prediction for churn rate using their Customer_Churn__c (Yes/No) field. In Einstein Prediction Builder, after selecting the object and prediction field, what is the next step?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Select the dataset (records to train on).

After selecting the prediction field (binary classification), you must select the dataset (records to train on) and then choose features (input fields) that the model will use to make predictions.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Define the prediction score field and explanation field.

    Why it's wrong here

    Score and explanation fields are configured later in the process.

  • Deploy the model to production.

    Why it's wrong here

    Deployment happens after training and validation.

  • Select the dataset (records to train on).

    Why this is correct

    After choosing the prediction field, you define the dataset (object and filters) to train the model.

  • Select features (input fields) to train the model.

    Why it's wrong here

    Features are selected after defining the dataset.

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