Can you provide some decision tree examples with solutions to help me better understand how they work?

Answer 1

Decision trees are a popular tool in machine learning for making decisions based on input data. Here are some examples to help you understand how they work:

1. Example: Predicting whether a customer will buy a product based on their age and income. Solution: The decision tree would split the data based on age and income, creating branches that lead to a final decision of whether the customer is likely to buy the product or not.

2. Example: Classifying emails as spam or not spam based on keywords. Solution: The decision tree would analyze the presence of specific keywords in the email to determine if it is spam or not.

3. Example: Predicting the likelihood of a student passing an exam based on study hours and previous grades. Solution: The decision tree would use study hours and previous grades as criteria to predict whether a student is likely to pass the exam.

These examples demonstrate how decision trees can be used to make predictions or classifications based on input data.