Explore MATLAB source code curated for "SVR" with clean implementations, documentation, and examples.
A parameter optimization program for libsvm that provides full grid search optimization specifically designed for SVR (Support Vector Regression), primarily used for SVM regression prediction with detailed implementation of parameter tuning algorithms and cross-validation techniques.
Implementation of feature selection techniques for SVR machine learning algorithms, featuring one filter-based method (CFS Correlation-based Feature Selection) and two wrapper methods (Genetic Algorithm GA and Particle Swarm Optimization PSO). The gridsearch module performs hyperparameter tuning for SVR optimization, while SVM_CV handles k-fold cross-validation procedures with customizable parameters.
Grey Wolf Optimizer (GWO) Enhanced Support Vector Machines and Support Vector Regression - Implementation and Performance Analysis
Support Vector Machine Regression (SVR) for 1D and 2D input features