Answer-first summary for fast verification
Answer: Yes
The solution meets the goal for several reasons: 1) It preserves dimensionality by not adding or removing columns/rows, only replacing missing values within existing columns. 2) The dataset is numerical, making median replacement appropriate and valid. 3) It enables analysis of the full dataset by filling all missing values. 4) Median is robust to outliers, making it suitable for numerical data. The community consensus strongly supports 'Yes' (90% of answers), with the top-voted comment (34 upvotes) clearly explaining that median replacement doesn't affect dimensionality (which refers to the number of features, not unique values) and satisfies the requirement to analyze the full dataset. While some argued for MICE as potentially better, the question asks if the proposed solution meets the goal, not if it's optimal, and median replacement does satisfy all stated requirements.
Author: LeetQuiz Editorial Team
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You are working with a numerical dataset containing missing values in multiple columns. Your goal is to clean the missing data using an appropriate method that preserves the dimensionality of the feature set, ensuring the entire dataset is available for analysis.
Proposed Solution: Replace the missing values in each column with the median value of that column.
Does this solution meet the goal?
A
Yes
B
No