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Thus, almost all (115 out of 119) of the isolates from areas outside North Wales were assigned to the same model cluster (cluster 1) with a probability of membership of greater than 0.75.
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This is, on average around 5 models per cluster; clusters contain 16 models on average.
The clusters (Cluster 2 and 3) including these two morbidities appeared in Model 2. In Model 3, the cardiopulmonary cluster (Cluster 3) had a stronger effect than that in Model 2. However, Cluster 2 dampened the effect via a cluster interaction with Cluster 3.
In addition, the conceptual meaningfulness and sizes of the clusters (the five-cluster model included one cluster with only 52 participants; data not shown) stressed the superiority of four-cluster solutions over the five-cluster model.
The clustering was achieved by first finding the model (the 'cluster center') with the largest number of neighboring models within the RMSD threshold, then assigning these models to the first cluster (cluster 0).
This paper introduces a systematic approach to reduce this discrepancy using data clustering, model selection, and cluster identification techniques.
(F ) Schematic representation of the sub-cluster model: a DCN cluster is divided into several overlapping subsets of neighboring neurons.
Fig. 5 a The fractal cluster simulated within the model of "cluster-cluster".
Simulation of fractal cluster growth was carried out from 1000 polydisperse nanoparticles within the model of "cluster-cluster" (Fig. 5 a), which corresponds to the natural growth of fractal aggregates in sols.
The Random-Cluster Model uses multipath clusters to model the radio channel.
In this work, we revisit this classical concept and suggest an alternative clustering model in which clusters function on datums sequentially.
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