🎯 K-Nearest Neighbors (KNN)

📚 What is K-Nearest Neighbors?

KNN is a simple yet powerful classification algorithm that predicts a point's class based on its K nearest neighbors. It's called "lazy learning" because it doesn't build a model during training.

How it works:

• Store all training data points with their labels
• When predicting, find the K closest points to the test point
• Use majority voting among those K neighbors
• Assign the most common class to the test point

Real-world applications:

• Recommendation systems (Netflix, Amazon)
• Image recognition and classification
• Credit rating prediction
• Pattern recognition in medical diagnosis