The High Dimensional Data Clustering (HDDC) toolbox contains an efficient unsupervised classifiers for high-dimensional data. This classifier is based on Gaussian models adapted for high-dimensional data. Reference: C. Bouveyron, S. Girard and

Clustering is the unsupervised classification of patterns (observations, data items, or feature vectors) into groups (clusters). The clustering problem has been addressed in many contexts and by researchers in many disciplines this reflects its

k-means is a algorithm for make unsupervised learning, which use a vector, value k for create the clustering