Classical PCA Face Recognition Method and PCA+SVM Face Recognition Approach
Implementation and Analysis of PCA-Based and PCA+SVM Hybrid Face Recognition Methods
MATLAB Implementation of PSO for SVM Parameter Optimization with Practical Examples
MATLAB Program for Particle Swarm Optimization of Support Vector Machine Parameters with Implementation Examples
Classical Data Mining Algorithms
Classical Data Mining Algorithms
Implementation Routines for Clustering and Classification Using SVM Algorithm
Support Vector Machine (SVM) algorithms for both classification and clustering tasks, with enhanced descriptions of implementation approaches and key functions
Kernel Methods and SVM: Essential Approaches in Pattern Recognition and Machine Learning
Kernel Methods and Support Vector Machines (SVM) are fundamental techniques in pattern recognition and machine learning, with wide-ranging applications in classification and regression tasks.
Comprehensive PSO-Optimized SVM Implementation
Comprehensive Particle Swarm Optimization for SVM Parameter Tuning
SVM Data Transformation and Preprocessing Methods
SVM Data Transformation and Processing Techniques with Code Implementation Insights
Data Classification and Prediction Using Support Vector Machines (SVM)
Implementation of SVM-based data classification prediction for wine type identification with feature selection and model optimization techniques