Answer-first summary for fast verification
Answer: No
The solution does not meet the goal because removing entire columns that contain missing values reduces the dimensionality of the feature set. The requirement explicitly states that the cleaning operation must not affect the dimensionality, meaning the number of features (columns) should remain unchanged. Removing columns eliminates features entirely, which contradicts this requirement. Community discussion confirms this with 100% consensus on answer B (No), with upvoted comments explaining that removing columns affects dimensions and is therefore incorrect. Appropriate methods for preserving dimensionality while handling missing values include imputation techniques like mean/median imputation or MICE, not column removal.
Author: LeetQuiz Editorial Team
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You are working with a numerical dataset that has missing values in multiple columns. You must clean the missing data using a method that preserves the original number of features in the dataset. The solution proposed is to remove any column that contains at least one missing value.
Does this solution achieve the goal?
A
Yes
B
No
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