DatabricksCertified Machine Learning Associate
Domain 2Objective 6
Impute Missing Values with the Mode, Mean, or Median Value MACHINE-LEARNING-ASSOCIATE Practice Questions (Page 1)
Part of the Section 2: Data Processing domain, which makes up ~27% of our current practice bank. Databricks does not publish an official question count, but from its 90-minute exam (~35–60 total, ~9–16 in this domain), expect 1–2 from this objective — we provide 12 practice questions to prepare you well beyond it. (estimate)
12questions here
3free pages
6concepts
Questions 1–5
- 1
Why is mode imputation appropriate for a discrete numeric column like 'number_of_rooms'?
Select an answer first - 2
Which imputation method is most appropriate for a categorical column with missing values?
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Which scikit-learn transformer can be used to impute missing values with the mean, median, or most frequent value?
Select an answer first - 4
A numerical column 'income' is heavily right-skewed. Which imputation method is most appropriate to fill its missing values?
Select an answer first - 5
A data scientist is preparing a dataset for a fraud detection model. The 'transaction_amount' column has 8% missing values and is heavily right-skewed, with most transactions under $100 but a few large transactions over $10,000. The scientist wants to impute the missing values. Which approach is most appropriate?
Select an answer first
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