Which of the following is not among the data preparation activities?

• A. Classification of data set using one of the existing data models
• B. Handling missing values
• C. Normalization
• D. Feature selection

Answer: (A)

Data preparation focuses on making the data ready for modeling by cleaning and transforming it. Handling missing values, normalizing features, and performing feature selection are all classic preparation steps that ensure the data is complete, on a comparable scale, and concise yet informative for learning algorithms. Classifying the data set using an existing data model, however, is a modeling step that applies a trained or chosen model to assign labels rather than preparing the data itself. So, the option about classification is not a data preparation activity.