Support Vector Machine Prediction Program

This program is a MATLAB-implemented Support Vector Machine (SVM) solution specifically designed for prediction and analysis tasks. It employs the Support Vector Machine algorithm - a robust machine learning method effective for handling both classification and regression problems. The program trains an SVM model using provided datasets through MATLAB's built-in functions like fitcsvm (for classification) or fitrsvm (for regression), then utilizes the trained model to predict outcomes for new unseen data. Key implementation features include kernel function selection (linear, RBF, polynomial), parameter optimization for regularization and kernel parameters, and cross-validation support for model evaluation. Applicable across diverse domains including finance, healthcare, and weather forecasting, the program offers a user-friendly interface enabling intuitive parameter configuration through GUI components and result visualization via MATLAB's plotting functions. Overall, it represents a powerful yet accessible tool that facilitates efficient predictive modeling and analytical workflows through structured code organization and modular function design.