This algorithm can lead to empty clusters and disrupt the parameters estimation. By adding a stochastic step for assigning observations to clusters. SEM: This is a stochastic version of the EM algorithm.EM: This is the standard algorithm used for inference in mixture models.XLSTAT offers the possibility to use three different inference algorithms to estimate the Gaussian parameters of the 14 models: Inference algorithms used in XLSTAT for mixture models It is also possible to force the mixing proportions to be equal.
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Mixture models in XLSTATīy controlling the covariance matrix according to the eigenvalue decomposition of Celeux et al., XLSTAT offers 14 different Gaussian mixture models. XLSTAT proposes the use of a mixture of Gaussian distributions. The aim of mixture models is to structure dataset into several clusters. These probabilities can also be used to interpret suspected classifications. The probability of belonging to each cluster is calculated and a classification is usually achieved by assigning each observation to the most likely cluster.
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