For datasets with categorical variables, the _______ method can be used to handle missing values by assigning a new category for missingness.
- Mean Imputation
- Mode Imputation
- Median Imputation
- Most Frequent Imputation
When dealing with missing values in categorical data, the most frequent imputation (Option D) method is used, which replaces missing values with the category that occurs most often in the column. This approach is suitable for handling categorical variables.
Loading...
Related Quiz
- For time-series data, which variation of gradient boosting might be more appropriate?
- The _______ activation function outputs values between 0 and 1 and can cause a vanishing gradient problem.
- A common problem in training deep neural networks, where the gradients tend to become extremely small, is known as the _______ problem.
- When you want to visualize geographical data with customizable layers and styles, which tool is commonly used?
- Which statistical measure represents the middle value in a dataset when it's ordered from least to greatest?