Titlebook: Classification and Data Science in the Digital Age; Paula Brito,José G. Dias,Rebecca Nugent Conference proceedings‘‘‘‘‘‘‘‘ 2023 The Editor

cortisol

Jackie Xiu Yan,Jun Pan,Honghua Wangional maximization algorithm (ECM). The performance of the proposed method is illustrated for simulated and real-world functional data, and CFunHDDC outperforms FunHDDC when applied to functional data with outliers.

Petechiae

Jackie Xiu Yan,Jun Pan,Honghua Wangvided in case of one and two covariates, under Gaussian assumptions and in presence of only one real response variable. This work aims to extend these results to a more complex setting where three independent variables are considered.

胰岛素

就职

Jackie Xiu Yan,Jun Pan,Honghua Wanghlet-multinomial components. We illustrate how this mixture structure can improve a microbiome data analysis to cluster patients into “enterotypes”, which are a classification based on the bacteriological composition of gut microbiota. The comparison between the two models is performed through an application to a real gut microbiome dataset.

peptic-ulcer

Nikolaos Chaniotakis,Magdalini Papazogloucterizes each block. Placing the estimate of the model parameters under the maximum likelihood approach, we derive a Variational Expectation–Maximization (VEM) algorithm for estimating the model’s parameters. The finality of the proposed VEM-LBRM is illustrated through simulated datasets.

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Vassilios Makrakis,Nelly Kostoulas-Makrakisined parsimonious model-based clustering have been introduced which include the 14 parsimonious models that are often applied in model-based clustering when assuming normal components as limit cases. In this paper we initially review the traditional approaches and illustrate through an example the benefits of the adoption of the new constraints.

hankering

Nicholas Zaranis,George M. Exarchakosnt exchanges represent the set of links between them. The Infomap community detection algorithm is then chosen for partitioning two-mode networks of students’ cohorts to discover different network patterns.

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Neuralgia

A Trivariate Geometric Classification of Decision Boundaries for Mixtures of Regressions,vided in case of one and two covariates, under Gaussian assumptions and in presence of only one real response variable. This work aims to extend these results to a more complex setting where three independent variables are considered.