Answer-first summary for fast verification
Answer: Yes
The solution meets the goal because: 1) It preserves dimensionality by not adding or removing columns/rows, only replacing missing values with existing column statistics. 2) It enables analysis of a full dataset by filling all missing values. 3) The dataset is explicitly numerical, making median replacement appropriate. 4) Community consensus strongly supports 'Yes' (90% of answers, highest upvoted comments), noting that median replacement is a valid Azure ML method that doesn't affect feature set dimensionality. While some argued for MICE as potentially better, the question asks if the solution meets the goal, not for the optimal method, and median replacement satisfies all stated requirements.
Author: LeetQuiz Editorial Team
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You are working with a numerical dataset that has missing values in multiple columns. Your goal is to clean the missing data using a 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 achieve the goal?
A
Yes
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B
No