Explore MATLAB source code curated for "核函数" with clean implementations, documentation, and examples.
MATLAB implementation and technical explanation of Gaussian kernel function, a fundamental tool in machine learning and data mining for non-linear data transformation
A comprehensive MATLAB program collection for implementing Support Vector Machines (SVM) and various kernel functions with practical code examples
The svkernel function serves as a kernel function and is straightforward to implement. By following the mathematical formula of kernel functions, one can easily write the corresponding code, typically involving common kernel types such as linear, polynomial, or radial basis functions.
Source code implementation of kernel-based principal component analysis algorithm for face recognition applications
Implementation of SVM data classification and regression analysis using various kernel functions including RBF, sigmoid, and polynomial kernels with code integration
This algorithm provides detailed descriptions of commonly used kernel functions and visualizes their characteristics through 3D graphical representations, including implementation insights for machine learning applications.
A detailed technical analysis covering libsvm's structural parameters, kernel functions, SVM prediction mechanisms, and training processes with code implementation insights
SVM-based data classification with customizable kernel functions for image segmentation operations. The program automatically trains classification planes, featuring flexible kernel selection and adaptive training algorithms.
This kernel-based partial least squares algorithm first applies a kernel function for nonlinear transformation of the original matrix, then solves the problem through nonlinear iterative optimization.
Implementation of kernel function-based C-means clustering image segmentation using MATLAB, featuring robust experimental performance and practical usability