This repository contains self-implemented fundamental machine learning classifiers and their usage on datasets.

📌 Features

• Custom Implementations:

  • 🏗️ k-Nearest Neighbors (KNN) classifier
  • 🧠 Perceptron algorithm
  • 🔄 One-vs-Rest (OVR) multiclass strategy

• Scikit-learn comparison:

  • 🌳 Random Forest
  • 🎒 Bagging Classifiers
  • 🚀 Boosting methods (AdaBoost, Gradient Boosting)

• Comprehensive Evaluation:

  • 📊 Accuracy, Precision, Recall, F1-score
  • 🤔 Confusion matrixes
  • 🎨 Decision boundary visualizations