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This article proposed a novel classification algorithm called LDABoost based on boosting ideology which uses Latent Dirichlet Allocation (LDA) to modeling the feature space.
Some statistical models [8 16] are developed for HRRP-based RATR, of which [14 16] successfully utilized the hidden Markov model (HMM) for modeling the feature vectors from the HRRP sequence.
Modeling the feature distribution with a bi-Gaussian model can be also used as a VAD, where the Gaussian with the lower mean corresponds to noisy frames [25].
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We consider a classifier based on Independent Component Analysis Mixture Modelling (ICAMM) to model the feature joint-probability density.
Subsequently, for each further feature, we fit a linear regression that modelled the feature's values over all experiments as a function of the already selected features.
Ma and Grimson [4] used a single Gaussian to model the features and a mixture of Gaussians (MoG) to model feature positions.
In this section, we modeled the features using Gaussian mixture model (GMM), which are widely used statistical classifier.
The model consists of the integrated platform system, information model, part model, geometric modelling and the feature model.
To evaluate the recognition rate achieved using mixture models, the feature vectors are fed into the GMM/SVM classifier.
(24 ) A CBS system shares with these models the feature of manual collection of excreta in relatively small containers.
Such masks were usually modeled over the features of the dead and cast in wax.
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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