Review:
Random Forest
overall review score: 4.5
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score is between 0 and 5
Random forest is a popular ensemble learning method in machine learning that builds multiple decision trees and merges them together to get a more accurate and stable prediction.
Key Features
- Ensemble learning
- Decision trees
- Bagging
- Feature selection
Pros
- Highly accurate predictions
- Reduces overfitting
- Handles large datasets well
- Built-in feature selection
Cons
- Can be slow for real-time predictions
- May not perform well with noisy data