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Google Professional Machine Learning Engineer

▤ 280 Questions◷ 120 Minutes✓ 70% Passing Score▣ Updated: Sep 2026

Question 152 of 280

Single answer
You are developing an ML model using a dataset with categorical input variables. You have randomly split half of the data into training and test sets. After applying one-hot encoding on the categorical variables in the training set, you discover that one categorical variable is missing from the test set. What should you do?
AUse sparse representation in the test set.
BRandomly redistribute the data, with 70% for the training set and 30% for the test set
✓CApply one-hot encoding on the categorical variables in the test data
DCollect more data representing all categories
✓
Correct Answer: C

Apply one-hot encoding on the categorical variables in the test data

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Explanation

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