Discuss the importance of data : Basics of decision trees

The video tutorial introduces decision trees, highlighting their interpretability and use in business decisions. It explains the structure of decision trees, including how they segment populations based on predictor variables. An example of predicting student scores using decision trees is provided, demonstrating the process of splitting data into regions. The tutorial also distinguishes between classification and regression trees, and covers key decision tree terminologies such as root node, splitting, and leaf nodes.

What is a key advantage of using a simple decision tree?

• High accuracy

• Requires less data

• Easy interpretation

• Complexity

In a decision tree, what is the purpose of splitting the population into regions?

• To simplify the model

• To increase the number of variables

• To identify distinct characteristics of predictor variables

• To reduce the size of the dataset

What characteristics define the first region in the decision tree example provided?

• Age less than 30 and eats a lot of pizza

• Age more than 30 and eats a lot of pizza

• Age more than 30 and does not eat pizza

• Age less than 30 and does not eat pizza

How does the decision tree example predict student scores?

• By analyzing the number of classes attended

• By evaluating the number of hours studied and midterm scores

• By assessing the student's participation in extracurricular activities

• By considering the student's age

What is the average score of students who study more than 10 hours according to the example?

• 82 marks

• 57 marks

• 39 marks

• 75 marks

Which type of decision tree is used for predicting categorical variables?

• Regression tree

• Root node

• Classification tree

• Decision node

What is a root node in a decision tree?

• A node that cannot be split further

• The node with the least data

• The node where the tree ends

• The first node containing the entire population

What is a decision node?

• The final node in a tree

• A node where splitting occurs

• A node with no data

• A node that cannot be split further

What is a leaf node in a decision tree?

• A node that contains the entire population

• A node that is not split further

• A node that is always at the top of the tree

• A node that can be split further

What is a subtree in the context of decision trees?

• A node that cannot be split

• A small section of the entire tree

• The entire decision tree

• The root node of the tree