Courseiva
Salesforce Einstein AI FeatureshardMultiple ChoiceObjective-mapped

AI Associate Salesforce Einstein AI Features Practice Question

An admin is using Einstein Prediction Builder to predict whether a case will escalate. They have selected the prediction field (binary) and the dataset. After training, they notice the model uses all available fields. What should they do to improve model performance and reduce noise?

⚠ Common exam trap

Candidates often assume Einstein Prediction Builder automatically handles feature selection or that increasing data always improves performance, when in fact the tool requires manual feature selection to reduce noise and avoid overfitting.

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 relevant features (input fields) and exclude irrelevant ones

Einstein Prediction Builder automatically includes all available fields by default during training, which can introduce noise and reduce model accuracy. By manually selecting only relevant features (input fields) and excluding irrelevant ones, the admin reduces dimensionality, minimizes overfitting, and improves the model's predictive performance. This feature selection step is a standard best practice in machine learning to ensure the model focuses on meaningful predictors.

Answer analysis

Option-by-option breakdown

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

  • Increase the dataset size

    Why it's wrong here

    More data may help but does not directly reduce noise from irrelevant fields.

  • Use a different algorithm by default

    Why it's wrong here

    Prediction Builder automatically chooses the algorithm based on data.

  • Select relevant features (input fields) and exclude irrelevant ones

    Why this is correct

    Feature selection improves model accuracy by removing noisy fields.

  • Change the prediction field to a different binary field

    Why it's wrong here

    The prediction field is the target; changing it changes the problem.

About these practice questions

This AI Associate question is part of Courseiva's 753-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →

How Courseiva writes practice questions · Editorial policy

JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This AI Associate practice question is part of Courseiva's free Salesforce certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI Associate exam.