Random Forest Algorithm

📘 Artificial Intelligence & Machine Learning Basics 👁 51 views 📅 Nov 05, 2025
⏱ Estimated reading time: 1 min

Definition:
A supervised learning algorithm that combines multiple decision trees to improve prediction accuracy and reduce overfitting.

Key Points:

  • Ensemble method: Many decision trees vote for the final prediction

  • Works for classification and regression

  • Reduces errors compared to a single decision tree

Applications:

  • Credit scoring

  • Stock market prediction

  • Fraud detection

Advantages:

  • High accuracy

  • Handles large datasets well

  • Less prone to overfitting

Limitations:

  • Complex and less interpretable than a single tree

  • Slower for real-time predictions


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