K-Nearest Neighbors (KNN) for Car Safety Classification 🚗

This project implements the K-Nearest Neighbors (KNN) algorithm to classify cars based on safety using the Car Evaluation Dataset from UCI Machine Learning Repository.

📌 Features

• Preprocesses categorical data using Label Encoding.
• Normalizes features using StandardScaler to improve distance calculations.
• Implements KNN Classification using Scikit-Learn.
• Optimizes hyperparameters using RandomizedSearchCV for best results.
• Evaluates model performance with accuracy, confusion matrix, and classification report.

📂 Dataset

• Source: UCI Machine Learning Repository
• Attributes:
  • Buying price
  • Maintenance cost
  • Number of doors
  • Passenger capacity
  • Luggage boot size
  • Safety level
  • Class (Target Variable)

Baseline Accuracy (Default KNN): 81.50%

Optimized Accuracy (Using RandomizedSearchCV): 92% 🚀