Using evolutionary algorithms for model-based clustering

In mixture model-based clustering, parameter estimation is generally carried out using the expectation–maximization algorithm, or some closely related variant. We present a new approach by casting the model-fitting problem as a single-objective evolutionary algorithm that focuses on searching the cluster-membership space. The appeal of an evolutionary algorithm is its ability to more thoroughly search the parameter space, providing an approach …