Sentence examples for clustering components from inspiring English sources

Unstructured heterogeneity had a greater influence on the IRR than spatial variation as assessed by the posterior mean of the heterogeneity and clustering components variance (data not shown) (Mollié, 1996).

Secondly, because the clustering components of the present method can abstract any sub-network very rapidly, any interactive function for producing network views of interest can be achieved if modules for selecting appropriate clusters/nodes are implemented.

I-TWEC has the lexical and semantic clustering components implemented as two consecutive phases.

Any subset of the entire network of particular interest to the researcher can be fed into the clustering components and the abstracted view of that cluster is displayed.

Sociobehavioral clustering itself was not related to CHD risk independent of the individual clustering components, suggesting it may be the individual sociobehavioral risk factors themselves (i.e., physical activity, diet, smoking and education) that are responsible for associations with CHD risk.

Objectives were to determine if sociobehavioral clustering is associated with biological CHD risk factors (total cholesterol, HDL cholesterol, systolic blood pressure, body mass index, waist circumference, and diabetes) and whether associations are independent of individual clustering components.

The actual sequence clustering component of SEED is an iterative process consisting of three major steps.

Our method consists of three components: an ultrafast graph clustering component, a property-based clustering component, and an interface that presents an abstracted view and permits researchers to flexibly choose nodes/clusters (Fig. 1).

The underlying components of NaviClusterCS are (i) an ultrafast graph clustering component, (ii) a property-based clustering component, and (iii) a visualization component that connects to the Cytoscape canvas.

The new clusters resulting from the property-based clustering are used in the next component instead of those generated by the ultrafast graph clustering component, thereby reducing the number of clusters on the screen.

We found in this study an insignificant small difference in the performance of the prediction models that automatically cluster components and the ones that use semantically clustered components instead.