Metoda taksonomii oparta na modelach mieszanych - Witek, Ewa (Model-Based Clustering, 2008)
In model-based clustering approach, the data are viewed as coming from a mixture of probability distributions, each representing a different cluster. Models with varying geometric properties are obtained through Gaussian components with different parameterizations and cross-cluster constraints. Partitions are determined by the EM algorithm for maximum likelihood, with initial values from agglomerative hierarchical clustering. Models are compared on the basis of Bayesian Information Criterion (BIC). The problems of determining the number of clusters and the clustering method are at the same time solved by choosing the best model.
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu = Research Papers of Wrocław University of Economics; 2008; Nr 7, s. 199-206