Random Forests - Explained

This video explains Random Forest in machine learning, a powerful ensemble learning method that improves prediction accuracy by combining multiple decision trees. Learn how decision trees work, why a single tree overfits, and how techniques like bagging (bootstrap sampling) and feature randomness reduce variance and create a more stable model. Perfect for understanding concepts like classification, overfitting, and majority voting in machine learning algorithms. *Related Videos* ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ K-Means Clustering: https://youtu.be/dyG9cj5RKL0 Support Vector Machines: https://youtu.b…