SVM Implementation for Multi-Class Classification

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Resource Overview

MATLAB source code for SVM-based multi-class classification implementing training algorithms including One-Against-All (OAA), One-Against-One (OAO), and BSVM2 quadratic programming algorithms

Detailed Documentation

This MATLAB-implemented source code provides Support Vector Machine (SVM) solutions for multi-class classification problems. The implementation includes three primary training algorithms: One-Against-All (OAA) which constructs multiple binary classifiers for each class versus all others, One-Against-One (OAO) that builds classifiers for every pair of classes, and the BSVM2 quadratic programming optimization algorithm for efficient margin maximization. The code features optimized parameter tuning interfaces and includes cross-validation routines for model evaluation. These algorithms enable effective training and classification of multi-category datasets through MATLAB's native optimization toolbox integration, with clear documentation on hyperparameter configuration and decision function implementation.

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