Explore MATLAB source code curated for "特征空间" with clean implementations, documentation, and examples.
Kernel Fisher Discriminant Analysis (KFDA) - A nonlinear extension of Fisher Discriminant Analysis where training samples are first mapped to a high-dimensional feature space F using nonlinear mapping φ, then standard Fisher Discriminant Analysis is performed in this kernel-induced space.
Implementation of color and texture combined feature space for Mean-shift tracking
Kernel Methods for Pattern Analysis - Techniques and Implementation
Pattern Recognition Assignment focusing on four classic nonparametric classification approaches: Mean Sample Method, Mean Distance Method, Nearest Neighbor (NN), and K-Nearest Neighbors (KNN), with code implementation insights.