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Browsing by Subject "Cluster analysis"
Now showing items 1-12 of 12
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(Springer, 2010-03)A clustering algorithm which is based on density and adaptive density-reachable is developed and presented for arbitrary data point distributions in some real world applications, especially in geophysical data interpretation. ...
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(Emerald, 2010-01)Ranked preference data arise when a set of judges rank, in order of their preference, a set of objects. Such data arise in preferential voting systems and market research surveys. Covariate data associated with the judges ...
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(2010-12-11)Network modeling can be approached using either discriminative or probabilistic models. In the task of link prediction a probabilistic model will give a probability for the existence of a link; while in some scenarios ...
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(Wiley, 2011-04)
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(Wiley, 2010-03)A new family of mixture models for the model-based clustering of longitudinal data is introduced. The covariance structures of eight members of this new family of models are given and the associated maximum likelihood ...
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(Oxford University Press, 2010-11-01)In recent years, work has been carried out on clustering gene expression microarray data. Some approaches are developed from an algorithmic viewpoint whereas others are developed via the application of mixture models. In ...
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(2009-03)Uncovering community structure is a core challenge in social network analysis. This is a significant challenge for large networks where there is a single type of relation in the network (e.g. friend or knows). In practice ...
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(2010-08-30)Non-Negative matrix factorization (NMF) has emerged as an important technique for simplifying high-dimension data into interpretable factors. NMF has the attractive characteristic that the factor matrices are naturally ...
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(2010-12-10)Applicants to degree courses in Irish colleges and universities rank up to ten degree courses from a list of over five hundred. These data provide a wealth of information concerning applicant degree choices. A Dirichlet ...
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(Wiley-Blackwell, 2012-08)The analysis of network data is an area that is rapidly growing, both within and outside of the discipline of statistics. This review provides a concise summary of methods and models used in the statistical analysis of ...
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(Sun SITE Central Europe (CEUR), 2010-09-24)A common task in many domains with a temporal aspect involves identifying and tracking clusters over time. Often dynamic data will have a feature-based representation. In some cases, a direct mapping will exist for both ...
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(2009-12)Many recent approaches to modeling social networks have focussed on embedding the actors in a latent “social space”. Links are more likely for actors that are close in social space than for actors that are distant in ...
Now showing items 1-12 of 12