Random Forest

An ensemble learning method that operates by constructing a multitude of decision trees.
Machine Learning
Classification
Ensemble Learning
Aggregated Decision Boundary
Controls
Data Generation
Number of Points: 200
Number of Classes: 2
Hyperparameters
Number of Trees: 20
Max Depth Per Tree: 10