Explore MATLAB source code curated for "支持向量机" with clean implementations, documentation, and examples.
A genetic algorithm implementation designed to optimize kernel function parameters and related hyperparameters for Support Vector Machines (SVM), featuring selection, crossover, and mutation operations with fitness evaluation through model performance metrics.
A custom Tri-training algorithm implementation leveraging Support Vector Machines, K-Nearest Neighbors, and Naive Bayes classifiers for collaborative training with code-level integration details
Main program implementation of Least Squares Support Vector Machines (LSSVM) featuring fundamental classification and regression capabilities with configurable kernel functions and optimization parameters
A comprehensive machine learning algorithm suite implemented on MATLAB platform, featuring neural networks, fuzzy logic, and support vector machines with robust code implementation and modular function design
A kernel-based multi-class classifier utilizing Support Vector Machines, designed for educational and research applications. Features code implementation details for classification algorithms and model training workflows.
My implementation of a Support Vector Machine for regression analysis, which allows users to design sample data and perform regression after downloading the program.
Implementation of image classification using the Sequential Minimal Optimization (SMO) algorithm for Support Vector Machines, featuring code-level insights into feature processing and optimization techniques.
Support Vector Machine implementation code with detailed algorithm explanations and MATLAB programming insights.
Wind power forecasting based on PSO-optimized SVM algorithm, employing Particle Swarm Optimization to enhance Support Vector Machine parameters for improved prediction performance.
MATLAB Support Vector Machine prediction with complete dataset, case analysis, and thoroughly debugged source code (original author's program personally verified). Requires libsvm toolbox installation prior to execution. Case study focuses on short-term electric power forecasting, demonstrating practical SVM implementation with parameter optimization techniques.