Applications:

• Five-year-old explanation
• Definition: A decision tree is a supervised machine learning algorithm that forms a tree structure to make predictions.
• Components:
  • Non-terminal nodes: Represent decisions on descriptive features.
  • Terminal (leaf) nodes: Represent predictions for the target feature.
• constructed with entropy and information gain

Applications:

• Predictive Modeling:
  • Predicts outcomes based on input features.
• Production Rule Extraction:
  • Describes patterns in the data.
  • Explains the decision-making process.