Results 11 to 20 of about 1,500,611 (328)
blockcluster: An R Package for Model-Based Co-Clustering [PDF]
Journal of Statistical Software, 2017 Simultaneous clustering of rows and columns, usually designated by bi-clustering, coclustering or block clustering, is an important technique in two way data analysis.
Parmeet Singh Bhatia +2 more
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Model-Based Clustering of Mixed Data With Sparse Dependence
IEEE Access, 2023 Mixed data refers to a mixture of continuous and categorical variables. The clustering problem with mixed data is a long-standing statistical problem. The latent Gaussian mixture model, a model-based approach for such a problem, has received attention ...
Young-Geun Choi, Soohyun Ahn, Jayoun Kim
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, 2019 Mixture models extend the toolbox of clustering methods available to the data analyst. They allow for an explicit definition of the cluster shapes and structure within a probabilistic framework and exploit estimation and inference techniques available for statistical models in general.
Brad Boehmke, Brandon Greenwell
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Model-based clustering for populations of networks [PDF]
, 2020 Until recently obtaining data on populations of networks was typically rare. However, with the advancement of automatic monitoring devices and the growing social and scientific interest in networks, such data has become more widely available.
Signorelli, Mirko, Wit, Ernst
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Estimation of the Number of Endmembers in Hyperspectral Images Using Agglomerative Clustering
Remote Sensing, 2020 Many tasks in hyperspectral imaging, such as spectral unmixing and sub-pixel matching, require knowing how many substances or materials are present in the scene captured by a hyperspectral image.
José Prades +3 more
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Summarizing Finite Mixture Model with Overlapping Quantification
Entropy, 2021 Finite mixture models are widely used for modeling and clustering data. When they are used for clustering, they are often interpreted by regarding each component as one cluster. However, this assumption may be invalid when the components overlap.
Shunki Kyoya, Kenji Yamanishi
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Seasonal Dynamics of Soil Fungal and Bacterial Communities in Cool-Temperate Montane Forests
Frontiers in Microbiology, 2019 Both fungal and bacterial communities in soils play key roles in driving forest ecosystem processes across multiple time scales, but how seasonal changes in environmental factors shape these microbial communities is not well understood. Here, we aimed to
Nobuhiko Shigyo +2 more
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Journal of Classification, 2016 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +1 more source
Journal of Statistical Software, 2018 The teigen R package is introduced and utilized for model-based clustering and classification. The tEIGEN family of mixtures of multivariate t distributions is formed via an eigen-decomposition of the component covariance matrices and subsequent ...
Jeffrey L. Andrews +3 more
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Model Based Clustering for Mixed Data: clustMD [PDF]
, 2015 A model based clustering procedure for data of mixed type, clustMD, is developed using a latent variable model. It is proposed that a latent variable, following a mixture of Gaussian distributions, generates the observed data of mixed type.
Gormley, Isobel Claire +1 more
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