PCA_SVM: Dimensionality Reduction with Principal Component Analysis

This implementation utilizes PCA for dimensionality reduction, preserving 90% of critical data variance through eigenvalue decomposition. The code includes comprehensive comments and comes with sample datasets, while allowing users to integrate custom data for flexible testing.