“…METHODS: A previously described Bayesian method developed for normally distributed biomarkers is applied to two flexible distributions; namely, a Student-t and a mixture of Dirichlet processes. Here, numerical studies assess the adequacy of the previous method with both distributions. …”
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“…In this paper, we propose a new topic model named multi-attribute latent dirichlet allocation (MA-LDA), in which the time and hashtag attributes of microblogs are incorporated into LDA model. …”
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“…We relate the new discriminative information measures to Bayesian classification probabilities and error rates, and exemplify their use in Bayesian analysis of Dirichlet process mixture models fitted via Markov chain Monte Carlo methods as well as using a novel Bayesian expectation–maximization algorithm. …”
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“…Our framework consists of classifiers trained using term frequency-inverse document frequency (TF-IDF) features and a second approach based on topics modeled using a Latent Dirichlet Allocation model (LDA) to reduce the dimensionality of the unstructured data. …”
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“…In this calling procedure, a Gaussian Mixture Model and a Dirichlet Process Gaussian Mixture Model are integrated to infer genotypes. …”
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“…For evaluation purposes, we employ the active learning strategy using both our novel topic detection method and a baseline topic model (i.e., Latent Dirichlet Allocation). Results obtained demonstrate that our method is able to achieve a high sensitivity of eligible studies and a significantly reduced manual annotation cost when compared to the baseline method. …”
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“…Ninety-three academic commentaries from ninety-three authors, along with their references and original papers, are analyzed by a latent Dirichlet allocation based natural language processing approach. …”
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“…The method is based on novel results for the smooth and discrete Hodge–Morrey–Friedrichs decomposition on manifolds with boundary and subdivides the WSS vector field into five components: gradient (curl-free), co-gradient (divergence-free) and three harmonic fields induced from the boundary, which are called the centre, Neumann and Dirichlet fields. First, an analysis of WSS in several simulated simplified phantom geometries (duct and idealized aorta) was performed in order to understand the nature of the five components. …”
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“…Various statistical methods have been proposed for similar applications including (1) the Gaussian hierarchical model, (2) the semi-parametric Bayesian hierarchical model with a Dirichlet process prior and (3) the non-parametric empirical Bayes approach of smoothing by roughening. …”
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“…The resultant articles (N = 7,710) were analyzed using the Latent Dirichlet Allocation algorithm and major topics were extracted. …”
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“…We identified signature taxonomic groups by performing linear discriminant analysis and effective size comparisons (LEfSe) and defined bacterial community types using Dirichlet multinomial mixture (DMM) models. Influenza infection was shown to be significantly associated with microbial composition of the nasopharynx according to the virus type and the vaccination status of the patient. …”
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“…We proposed a framework named as LDAP, which combined the latent Dirichlet allocation model and affinity propagation algorithm to extract research topics from 95,876 AD-related papers published from 2007 to 2016. …”
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“…A total of 20,925 publications from the Web of Science database mentioning interventions and treatment in reducing the burden of childhood overweight and obesity on physical health, mental health, and society published in the period from 1991 to 2018 were in the analysis. We used Latent Dirichlet Allocation (LDA) for identifying the topics and a dendrogram for research disciplines. …”
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“…This study concluded that Latent Dirichlet Allocation (LDA) is feasible and appropriated to derive topics (focus) from messages posted to the autism support groups on Facebook. …”
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“…The paper has a particular focus on the Fourier coefficients of the periodic fluctuations: they are expressed as residues of the corresponding Dirichlet generating function. This makes it possible to compute them in an efficient way. …”
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“…Using a dataset of tweets with the hashtag “#Diet” or “#FoodDiet” (n = 10.591), we first use a Latent Dirichlet Allocation (LDA) model to identify the food categories most discussed on Twitter. …”
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“…We apply a recent advanced smoothing method called Hierarchical Dirichlet Process (HDP) to PETs, and then propose a novel hierarchical smoothing approach called Hierarchical Gradient Smoothing (HGS) as an alternative. …”
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“…The STM is a probabilistic extension of Latent Dirichlet Allocation (LDA), which allows the consolidation of document-level covariates. …”
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“…We have also improved the prediction accuracy by replacing multiclass classification with ordinal regression and Latent Dirichlet Allocation models with Correlated Topic Models. …”
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“…This textual analysis of 5780 publications extracted from the Web of Science, Medline, and Scopus databases was performed to explore the current research foci and propose further research agenda. The Latent Dirichlet allocation was used for topic modeling. Regression analysis was conducted to examine country variations in the research foci. …”
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