How does a decision tree work?
An example of an AI chatbot conversation about decision trees and their functionality.
Can you explain how a decision tree works?
Sure! A decision tree is a flowchart-like structure used for decision-making. It splits data into branches based on feature values.
What are the main components of a decision tree?
The main components are nodes (decision points), branches (possible outcomes), and leaves (final decisions or classifications).
How is a decision tree built?
A decision tree is built using algorithms like ID3 or CART, which select the best features to split the data at each node.
What are the advantages of using decision trees?
They are easy to understand, require little data preprocessing, and can handle both numerical and categorical data.
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