Decision Trees
📘 Artificial Intelligence & Machine Learning Basics
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📅 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:
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Tree structure: Root → Branch → Leaf
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Root: Main feature
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Leaf: Predicted outcome
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Splitting is based on criteria like Gini Index, Entropy, or Variance
Applications:
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Loan approval
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Customer segmentation
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Medical diagnosis
Advantages:
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Easy to understand and interpret
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Handles both numerical and categorical data
Limitations:
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Prone to overfitting
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Can be unstable with small data changes
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