New Data Mining Methods: Support Vector Machine Algorithm Examples
This book provides practical algorithm examples for Support Vector Machines, offering valuable learning assistance with code implementation demonstrations.
MATLAB Implementation of Support Vector Machine with Code Examples
MATLAB-based implementation of Support Vector Machine (SVM) that automatically performs data classification tasks using built-in functions and customizable parameters.
Support Vector Machine (SVM) Computation Program
This program implements Support Vector Machine calculations with full functionality, personally validated through experimental testing. The implementation includes core SVM algorithms for classification tasks.
Support Vector Machine and Kernel Function Toolkit
A comprehensive MATLAB toolkit featuring support vector machines and kernel functions with direct calling capabilities
Support Vector Machine for Language Classification Implemented in MATLAB
A MATLAB-based support vector machine implementation designed for language classification, featuring efficient text processing and multi-class recognition capabilities
Particle Swarm Optimization for Tuning Support Vector Machine Model Parameters
This MATLAB code implements a cost-sensitive Support Vector Machine (SVM) model optimized by Particle Swarm Optimization (PSO) algorithm, specifically designed for handling imbalanced datasets through automated parameter tuning.
Support Vector Machine Classification Algorithm Implementation
Implementing support vector machine classification algorithm using MATLAB, with comprehensive data training and testing procedures to achieve accurate data categorization
Support Vector Machine as a Novel Regression Approach
Support Vector Machine serves as an innovative regression method, particularly effective for nonlinear patterns. This implementation provides nonlinear regression capabilities using SVM with kernel functions and optimization algorithms to handle complex data relationships.
MATLAB Implementation of Support Vector Machine with SMO Algorithm
MATLAB implementation (pseudocode) of Support Vector Machine using Sequential Minimal Optimization (SMO) algorithm for efficient training and classification
Machine Learning Algorithms Software Package
A comprehensive machine learning algorithm package featuring neural networks, fuzzy logic, and support vector machines, implemented on the MATLAB platform with structured code organization and modular function design.