gmeans
G-Means clustering algorithm, an extended K-Means which tries to automatically determine the number of clusters by normality test. The G-means algorithm is based on a statistical test for the hypothesis that a subset of data follows a Gaussian distribution. G-means runs k-means with increasing k in a hierarchical fashion until the test accepts the hypothesis that the data assigned to each k-means center are Gaussian.
====References:====
G. Hamerly and C. Elkan. Learning the k in k-means. NIPS, 2003.
Parameters
data
the data set.
k
the maximum number of clusters.