Decision Trees: Advantages and Disadvantages

They generate understandable rules (correct)

They are computationally expensive to train

They are not capable of handling regression problems

They require a large amount of computation

They perform classification without requiring much computation

They are capable of handling both classification and regression problems

They are less appropriate for regression tasks (correct)

They are not prone to errors in classification problems

To reduce the accuracy of the model

To add more features to the model

To increase the complexity of the model

To remove unwanted branches of the tree to reduce complexity (correct)

<p>In classification problems with many classes and a relatively small number of training examples</p> Signup and view all the answers

<p>They are computationally expensive to train</p> Signup and view all the answers