In an MLflow pipeline, a data scientist applies `StandardScaler` to normalize features and then fits a `RandomForestClassifier`. Which statement correctly describes the roles of these two components?

StandardScaler is a transformer; RandomForestClassifier is an estimator.

Both are transformers because they both modify the input data.

Both are estimators because they both have a `fit()` method.

StandardScaler is an estimator; RandomForestClassifier is a transformer.

A data scientist needs to build a binary classification model on a dataset with 10,000 features and 500 samples. The goal is to identify the most important features for a subsequent analysis. Which algorithm is most appropriate for this scenario?

Logistic Regression with L1 regularization

Linear Discriminant Analysis (LDA)

A financial firm is predicting stock prices. They have two models: Model A has an RMSE of $5 and an MAE of $3. Model B has an RMSE of $6 and an MAE of $2. The firm's trading strategy is sensitive to large prediction errors, as they can trigger large losses. Which model should they choose?

Model B, because its lower MAE indicates it is more accurate on average.

Model A, because RMSE is always the best metric for financial predictions.

Model B, because its lower MAE means it is more consistent.

Model A, because its lower RMSE indicates it better controls large errors.

A data scientist is building a model to predict house prices. The business requirement is to minimize the impact of large prediction errors, such as underestimating the price of a luxury home by $500,000. Which regression metric should be used for model selection?

MAPE (Mean Absolute Percentage Error)

DatabricksCertified Machine Learning Associate

Domain 3Objective 1

Model Selection and Evaluation MACHINE-LEARNING-ASSOCIATE Practice Questions (Page 3)

Part of the Section 3: Model Development domain, which makes up ~23% of our current practice bank. Databricks does not publish an official question count, but from its 90-minute exam (~35–60 total, ~8–14 in this domain), expect 2–4 from this objective — we provide 22 practice questions to prepare you well beyond it. (estimate)

22questions here

5free pages

7concepts

Questions 11–15

11foundation · easy
In an MLflow pipeline, a data scientist applies `StandardScaler` to normalize features and then fits a `RandomForestClassifier`. Which statement correctly describes the roles of these two components?
Select an answer first
12foundation · easy
A data scientist needs to build a binary classification model on a dataset with 10,000 features and 500 samples. The goal is to identify the most important features for a subsequent analysis. Which algorithm is most appropriate for this scenario?
Select an answer first
13foundation · easy
A data scientist is evaluating a binary classifier that outputs probability scores. Which metric directly measures the difference between the predicted probabilities and the true binary labels, penalizing confident incorrect predictions more heavily?
Select an answer first
14expert · hard
A financial firm is predicting stock prices. They have two models: Model A has an RMSE of $5 and an MAE of $3. Model B has an RMSE of $6 and an MAE of $2. The firm's trading strategy is sensitive to large prediction errors, as they can trigger large losses. Which model should they choose?
Select an answer first
15foundation · easy
A data scientist is building a model to predict house prices. The business requirement is to minimize the impact of large prediction errors, such as underestimating the price of a luxury home by $500,000. Which regression metric should be used for model selection?
Select an answer first

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