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The acoustical classification step uses a Gaussian Mixture Models to classify the sounds according to the 7 predefined classes.
We then show how a statistical model selection strategy may be used with the finite mixture models to provide a data-adaptive choice of spatial scale, varying by location (i.e., multiscale), from which classifications at least as accurate as those of any single spatial scale may be achieved.
This problem could be addressed by using Dirichlet process mixture models to find a proper C for new datasets.
The ANN parameters are trained to fit the responses of the eHMM mixture models to the training data labels.
The recognition system uses Gaussian mixture models to model 165 different bird syllables, produced by 95 bird species.
In this study, we applied the mixture models to investigate PD in the mathematics test of a German LSA.
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The two clusters were extracted by fitting a Gaussian mixture model to the data (n = 433 units from 13 mice).
By fitting our mixture model to these data (Supplementary equations 9 11), we can re-cover the underlying mixture concentrations, despite the littoral end member consisting of terrestrial resources.
To identify at-sea behaviour, we fitted a Gaussian mixture model to speed and turning angles calculated for the tracks as in Fayet et al.22.22
(2004), by using a five-component mixture model to represent various differential expression patterns.
In this statistical model, I apply a clustering algorithm called the Gaussian mixture model to an aggregation of expert ranking data provided by Fantasypros.com.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com