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Expectation Maximization models the data as mixture of Gaussians, i.e. each cluster is represented by one Gaussian distribution.
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We developed a method based on treating the data as a mixture of normal components, and within a specific probability model we computed the posterior probability that each gene arose from any of these components, following the prescripts of model-based mixture clustering (McLachlan and Peel, 2000).
Also, the basic idea of generalized product kernels can be easily extended to other more complicated situations of mixed data types such as mixtures of continuous, ordered and unordered categorical variables.
When you're reading online, look for a mixture of statistics and data, as well as opinions.
Specifically, the MDA classifier estimates, from the training data, densities for each of the good and poor prognosis phenotypes as mixtures of two Gaussians.
This model specification covers mixtures of LMs as well as mixtures of LAMs.
(Unintentionally produced PCBs also typically occur as mixtures of congeners).
Although various problems are inherent in these data, such as the mixture of referral and primary institutions and inconsistencies in data completeness or quality, this database has supported many studies that would not have been possible otherwise.
Model-based approaches model microarray data as a linear mixture of latent variables that may correspond to specific biological sources.
Basically, Gaussian Mixture Models (GMM) treats the data by a mixture of multiple Gaussian components.
All this data suggests the mixture of two triterpenes.
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CEO of Professional Science Editing for Scientists @ prosciediting.com