Random Forest Algorithm
📘 Artificial Intelligence & Machine Learning Basics
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📅 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:
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Ensemble method: Many decision trees vote for the final prediction
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Works for classification and regression
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Reduces errors compared to a single decision tree
Applications:
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Credit scoring
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Stock market prediction
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Fraud detection
Advantages:
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High accuracy
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Handles large datasets well
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Less prone to overfitting
Limitations:
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Complex and less interpretable than a single tree
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Slower for real-time predictions
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