Random Forest
An ensemble machine learning method
About Random Forest
Random Forest is a method that operates by constructing multiple decision trees during training and outputting the class that is the mode of the classes (classification) or mean prediction (regression) of the individual trees.
Key Features:
- Reduces overfitting compared to single decision trees
- Handles both classification and regression tasks
- Can handle large datasets with higher dimensionality
- Provides feature importance estimates