Explore MATLAB source code curated for "SVM" with clean implementations, documentation, and examples.
Statistical pattern recognition methods in pattern recognition, including classical approaches like Bayesian methods, statistical learning, LDA, PCA, and SVM, provide an invaluable algorithmic toolbox with code implementation insights.
MATLAB implementation of SVM utilizing genetic operators for optimized parameter selection of C and G parameters.
MATLAB-based SVM program for time series forecasting with enhanced algorithmic implementation details
Twin Support Vector Machine (TWSVM/TSVM) is a variant algorithm of Support Vector Machines, specifically designed for binary classification tasks. This implementation includes MATLAB/Python code examples suitable for beginners, featuring dual hyperplane generation and non-parallel decision boundary approaches.
Source code for classification and function regression using Support Vector Machines (SVM), including practical examples that can be easily adapted through straightforward modifications.
Implementing wind speed prediction with Support Vector Machine (SVM) in MATLAB using custom-written code, featuring discussions on parameter configuration, feature engineering, and comparative performance analysis
MATLAB code for SVM with cross-validation, featuring simple implementation and practical usage for machine learning applications
SVM-based data classification with customizable kernel functions for image segmentation operations. The program automatically trains classification planes, featuring flexible kernel selection and adaptive training algorithms.
SVM applied to face recognition with satisfactory performance! MATLAB implementation for educational purposes with practical coding examples.
SVM multiclass classifier implementation featuring multi-class classification capabilities enhanced with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for parameter optimization