matzewolf/kMeans

k-means (unsupervised learning/clustering) algorithm implemented in MATLAB.

Cluster_2D_Visualization.m is a script that generates random (uniformly) distributed data points, runs both kMeans.m and MATLAB's built-in kmeans function, measures and compares their performance (i.e. computing time) and visualizes the final clusters and the distribution of the data points in the clusters in a histogram.
kMeans.m implements k-means (unsupervised learning/clustering algorithm). Technical Details:
The initial centroids are randomly selected out of the set of all data points (every data points maximum once).
The stopping condition is that no changes to any cluster is made.
clustering_app.mlapp opens an App with GUI where you can randomly generate data points and cluster them. You can re-hit all buttons to see the randomness in both point generation and the clustering algorithm.
clustering_app.mlappinstall installs the MATLAB App in the MATLAB Editor.