Results 11 to 20 of about 797,470 (304)
Model-based Methods of Classification: Using the mclust Software in Chemometrics [PDF]
Journal of Statistical Software, 2007 Due to recent advances in methods and software for model-based clustering, and to the interpretability of the results, clustering procedures based on probability models are increasingly preferred over heuristic methods. The clustering process estimates a
Chris Fraley, Adrian E. Raftery
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Parametric model-based clustering [PDF]
SPIE Proceedings, 2005 Parametric, model-based algorithms learn generative models from the data, with each model corresponding to one particular cluster. Accordingly, the model-based partitional algorithm will select the most suitable model for any data object (Clustering step}, and will recompute parametric models using data specifically from the corresponding clusters ...
Nikulin, Vladimir, Smola, Alexander
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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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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.
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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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Partial mixture model for tight clustering of gene expression time-course [PDF]
, 2008 Background: Tight clustering arose recently from a desire to obtain tighter and potentially more informative clusters in gene expression studies. Scattered genes with relatively loose correlations should be excluded from the clusters.
Li Chang-Tsun +8 more
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What Drives Consumers in Poland and the Czech Republic When Choosing Engine Oil Brand?
Entrepreneurial Business and Economics Review, 2019 Objective: The objective of the research was to study consumer decision-making and purchasing preferences when buying engine oils to reveal the presence of consumer preference heterogeneity.
Artur Wolak +3 more
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