MATLAB Toolbox for Support Vector Machines

I am delighted to introduce a sophisticated MATLAB toolbox specifically designed for Support Vector Machines (SVM). This toolkit provides robust classification capabilities using SVM algorithms with kernel functions (linear, polynomial, RBF) for pattern recognition, alongside regression fitting features for predictive modeling. The implementation includes parameter optimization routines for hyperparameter tuning and cross-validation modules to ensure model reliability. Whether you're a student exploring machine learning fundamentals or a researcher developing advanced predictive models, this toolbox serves as an invaluable resource with well-documented code structure and practical examples. The package contains essential functions for data preprocessing, model training with quadratic programming optimization, and result visualization - all implemented through MATLAB's object-oriented framework. Download now to embark on your machine learning journey with professionally crafted SVM implementations!