Decision Trees

📘 Artificial Intelligence & Machine Learning Basics 👁 82 views 📅 Nov 05, 2025
⏱ Estimated reading time: 1 min

Definition:
A supervised learning algorithm used for classification and regression. It splits data into branches based on feature values to make decisions.

Key Points:

  • Tree structure: Root → Branch → Leaf

  • Root: Main feature

  • Leaf: Predicted outcome

  • Splitting is based on criteria like Gini Index, Entropy, or Variance

Applications:

  • Loan approval

  • Customer segmentation

  • Medical diagnosis

Advantages:

  • Easy to understand and interpret

  • Handles both numerical and categorical data

Limitations:

  • Prone to overfitting

  • Can be unstable with small data changes


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