Which correctly describes classification?

Which correctly describes classification?

• A. Classification develops algorithms to develop rules to apply to new data.
• B. Classification assigns members of a dataset into categories based on known characteristics.
• C. Classification predicts a numerical value given characteristics of each member of a dataset.
• D. Classification explores data to find groups with common and previously unknown characteristics.

Answer: (B)

Classification is about assigning each item to one of predefined categories based on its characteristics. It uses labeled data to learn a mapping from features to category labels, so new observations can be placed into the correct category. This is a supervised learning task focused on categorization. The description that captures this idea—putting members of a dataset into categories based on known characteristics—is the best fit. In contrast, predicting a numerical value is regression, clustering looks for unknown groupings without predefined labels, and simply describing rule-building is too broad and doesn’t specify assigning to predefined classes.

Classification is about assigning each item to one of predefined categories based on its characteristics. It uses labeled data to learn a mapping from features to category labels, so new observations can be placed into the correct category. This is a supervised learning task focused on categorization. The description that captures this idea—putting members of a dataset into categories based on known characteristics—is the best fit. In contrast, predicting a numerical value is regression, clustering looks for unknown groupings without predefined labels, and simply describing rule-building is too broad and doesn’t specify assigning to predefined classes.