Question

Which statement correctly describes the use of regression and classification trees based on the nature of the dependent variable?

• A. Regression trees are suitable for continuous dependent variables, while classification trees are suitable for categorical dependent variables.
• B. Classification trees are suitable for continuous dependent variables, while regression trees are suitable for categorical dependent variables.
• C. Both regression and classification trees are suitable for continuous dependent variables.
• D. Both regression and classification trees are suitable for categorical dependent variables.

Hint:

Regression trees = continuous output; Classification trees = categorical output.

Answer 1

The Correct Option is A

Decision tree algorithms can be used for both regression and classification tasks.
When the target or dependent variable is continuous (like predicting house prices or temperature), regression trees are used.
When the target variable is categorical (like predicting whether an email is spam or not), classification trees are used.
Therefore, option (A) correctly matches regression with continuous output and classification with categorical output.
Options (B), (C), and (D) mix up the nature of dependent variables or do not correctly describe the separation of use cases.
Hence, the correct answer is option (A).