MDL - Based Selection of theNumber of Components in Mixture
نویسندگان
چکیده
A new method is proposed for selection of the optimal number of components of a mixture model for pattern classiication. We approximate a class-conditional density by a mixture of Gaussian components. We estimate the parameters of the mixture components by the EM (Expectation Maximization) algorithm and select the optimal number of components on the basis of the MDL (Minimum Description Length) principle. We evaluate the goodness of an estimated model in a trade-oo between the number of the misclassiied training samples and the complexity of the model.
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تاریخ انتشار 1998