Explore MATLAB source code curated for "Kmeans聚类" with clean implementations, documentation, and examples.
MATLAB implementation of Particle Swarm Optimization algorithm applied to optimize K-means clustering. Successfully tested on MATLAB 6.5/7.1 versions (other versions not verified). The code integrates PSO's global search capabilities with K-means clustering to achieve improved clustering accuracy and performance.
Color image segmentation with excellent performance. This function applies k-means clustering to input RGB images (dimensions m x n x 3). It requires two primary inputs: IMGIN (input image) and NCLUSTERS (number of clusters), and implements an interactive color segmentation workflow using k-means algorithm with user-defined color selection through interactive prompts.
KMeans clustering with predetermined cluster number, employing multiple algorithm runs to identify optimal initial configurations through distance-based centroid optimization