Data Encoding
Data Imputation
Data Transformation
Data Standardization
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Answer is Wrong!
The correct answer is A. Data Encoding.
Data encoding is the process of converting data from one form to another. In the context of categorical data, encoding involves converting categories into numbers. This can be done in a number of ways, such as assigning each category a unique integer value or using a code to represent each category.
Data encoding is often used in machine learning and data analysis. It can help to improve the accuracy of machine learning models and to make data analysis more efficient.
Here are brief explanations of the other options:
- Data Imputation is the process of filling in missing values in a dataset.
- Data Transformation is the process of changing the form of data without changing its meaning.
- Data Standardization is the process of converting data into a common format.