Support Vector Machine (SVM) MATLAB 2.51 Toolbox
MATLAB 2.51 Toolbox for Support Vector Machine (SVM) implementation, shared for community usage with enhanced code integration features.
MATLAB Code Implementations for Support Vector Machines (SVM)
Comprehensive MATLAB code implementations for SVM with detailed explanations of kernel functions and model evaluation techniques.
SVM Toolbox for Image and Hyperspectral Image Processing
A MATLAB-based SVM toolkit designed for image processing and hyperspectral image analysis, featuring implementation of core classification algorithms and spectral data handling capabilities.
Implementation of Text Classification Using K-Nearest Neighbors (KNN), Naive Bayes (NB), and Support Vector Machine (SVM) Algorithms
This assignment implements text classification using K-Nearest Neighbors (KNN), Naive Bayes (NB), and Support Vector Machine (SVM) algorithms, complete with datasets and a detailed experimental report covering implementation methodologies, performance analysis, and comparative evaluation of each approach.
Classic Support Vector Machine (SVM) for Classification
A MATLAB implementation of classic Support Vector Machine (SVM) for classification tasks, featuring identification, categorization, and parameter optimization capabilities with detailed algorithmic explanations.
Aircraft Target Recognition Using Support Vector Machine Classification on One-Dimensional Range Profiles
High Resolution Range Profile (HRRP) processing with Support Vector Machine (SVM) implementation for aircraft target classification. This comprehensive code example demonstrates complete workflow from feature extraction to classification, serving as an excellent learning routine for radar target recognition applications.
SVM Data Transformation and Preprocessing Methods
Methods for data transformation and normalization functions in SVM, including key preprocessing techniques and implementation approaches
PSO Toolbox Program: Parameter Optimization for SVM and ANN Models
The PSO Toolbox program has successfully passed test function validation and can be effectively utilized for parameter optimization in Support Vector Machines (SVM) and Artificial Neural Networks (ANN).
LDA+SVM Classification Program
A classification program combining Linear Discriminant Analysis and Support Vector Machine algorithms
Face Feature Extraction and Recognition Implementation Using SVM
Face feature extraction and recognition using Support Vector Machine (SVM) implemented in MATLAB, complete with performance analysis and detailed results evaluation.