Review:
Random Forest Classifier
overall review score: 4.5
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score is between 0 and 5
Random forest classifier is a machine learning algorithm that uses an ensemble of decision trees to make predictions.
Key Features
- Ensemble of decision trees
- Bootstrapping
- Feature randomization
Pros
- Highly accurate predictions
- Handles large data sets well
- Reduces overfitting compared to individual decision trees
Cons
- Can be computationally expensive to train
- May not perform well on very noisy data