🌲 Ensemble Methods

This repository contains implementations and experiments with some of the most widely used ensemble learning algorithms in Machine Learning using Scikit-learn.

📌 Implemented Methods

• ✅ Voting Classifier (Hard & Soft Voting)
• ✅ Bagging Classifier
• ✅ Random Forest Classifier (along with feature importance and OOB score)
• ✅ AdaBoost
• ✅ Gradient Boosting Regressor
• ✅ Gradient Boosting Classifier

🛠️ Technologies Used

• NumPy
• Pandas
• Matplotlib
• Scikit-learn

🎯 Objectives

• Understand how ensemble methods improve model performance.
• Compare different ensemble techniques.
• Learn their strengths, limitations, and practical applications.

🚀 Future Additions

• Boosting Algorithms (AdaBoost, Gradient Boosting)
• Extra Trees
• Stacking

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