Crime Pattern Analysis & Prediction

This project focuses on analyzing and predicting crime patterns using machine learning techniques. It combines clustering (KMedoids, Hierarchical) with classification models (Decision Tree, Random Forest) to explore hidden structures in crime data. The pipeline includes data preprocessing, dimensionality reduction using PCA, and comprehensive evaluation using metrics like silhouette score, Davies-Bouldin, and accuracy.