Explore MATLAB source code curated for "SVM算法" with clean implementations, documentation, and examples.
A hybrid classifier combining K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) algorithms, implementing ensemble learning techniques for enhanced classification performance
This project implements an SVM-based image classification system to automatically distinguish between basketball courts and tennis courts. The implementation includes color moment-based feature extraction for color images, complemented by HOG (Histogram of Oriented Gradients) and LBP (Local Binary Pattern) algorithms for enhanced feature representation. The workflow incorporates preprocessing steps like noise reduction and image enhancement to ensure input quality consistency.
Implementation of SVM Algorithm in Data Mining Using MATLAB - Complete guide with code examples and algorithm explanations
This project implements a Support Vector Machine (SVM) algorithm in MATLAB, performing binary classification between two distinct point classes and presenting graphical visualization of the classification results. The implementation includes key SVM components such as kernel function selection, optimization using quadratic programming, and margin calculation.
Pattern recognition and classification of iris dataset using Support Vector Machine (SVM) algorithm with MATLAB implementation details
A fingerprint recognition program implemented in MATLAB that performs Gabor filtering, binarization, erosion and other preprocessing operations on fingerprint images, utilizing SVM algorithms to determine whether new fingerprint images exist in the original database. Suitable for demonstrating small-scale fingerprint identification systems with detailed implementation approaches for image processing and machine learning components.
Implementation of clustering and classification routines using SVM algorithm. Includes experimental datasets, execution results, and a classic reference paper titled "A New Fuzzy Cover Approach to Clustering". Code enhancements demonstrate feature scaling, kernel selection, and hyperparameter optimization techniques.
Comprehensive MATLAB implementation of Support Vector Machine (SVM) algorithm featuring practical examples, technical documentation, and detailed explanations on data classification using MATLAB's built-in functions and custom code implementations
Comprehensive guide to implementing Support Vector Machine (SVM) algorithm in MATLAB with detailed code descriptions and practical applications