Construction and selection of a finite mixture model for use in clustering and vector quantization

摘要

A model selection process for selecting a finite mixture model that is suitable for a given task is described. A set of finite mixture models (FMMs) is produced from a set of parameter values and training data for a given task using an Expectation Maximization (EM) process. An FMM from the set of FMMs is selected based on a minimum description length (MDL) value calculated for each of the FMMs.