Decision Tree Structure

In this class, the teacher delves deeper into decision trees, building on the previous lesson. The video covers the main components of decision trees, such as nodes and branches, and explains their structure. An example of predicting car range is used to illustrate these concepts. The teacher also discusses the varying complexity of decision trees, which can range from a few branches to over a hundred, depending on the problem. The intricacies of node selection and tree depth are mentioned as topics for future classes.

What was the main topic discussed in the previous class?

• Genetic Algorithms

• Decision Trees

• Support Vector Machines

• Neural Networks

What is the starting point of a decision tree called?

• Branch

• Internal Node

• Leaf Node

• Root Node

Which of the following is NOT a component of a decision tree?

• Root Node

• Trunk Node

• Leaf Node

• Internal Node

In the car range prediction example, what was identified as the root node?

• Number of Cylinders

• Low Range

• High Range

• Weight

How can the size of decision trees vary?

• They are always the same size

• They can have between 10 and 20 branches

• They can range from a few branches to over 100

• They are always less than 10 branches