Databricks Certified Machine Learning - Associate
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You are working on a dataset with a categorical feature 'Education Level' that has three possible values: 'High School', 'Bachelor's Degree', and 'Master's Degree'. You have decided to impute the missing values with the mode value. Describe the process of imputing missing values with the mode value and explain why this approach is appropriate in this scenario.
A
The mode value is the value that appears most frequently in the 'Education Level' feature. Imputing missing values with the mode is appropriate because it represents the most common education level in the dataset.
B
The mode value is the average of all the unique values in the 'Education Level' feature. Imputing missing values with the mode is not appropriate, as it does not represent any actual education level.
C
The mode value is the median of all the unique values in the 'Education Level' feature. Imputing missing values with the mode is not appropriate, as it does not consider the distribution of the education levels.
D
The mode value is the minimum value in the 'Education Level' feature. Imputing missing values with the mode is not appropriate, as it may not represent the most common education level.