Sentence examples for cluster structure of from inspiring English sources

This enables the exploration of the cluster structure of the data through the examination of the values of the encoding coefficients and therefore, NMF is often used as a popular tool for clustering analysis.

Visual assessment of cluster tendency (VAT) reorders a similarity matrix to reveal the cluster structure of a data set, and a VAT-based clustering discovers clusters by image segmentation techniques.

The improvement was attributed to the morphology change: the tapered structure of the MWCNTs generated by the plasma etching and the increased inter-tip distance due to the cluster structure of the thin tips.

Taking advantages of the unique flower like structure of Ni-Co-Fe-S ultrathin nanosheets and cluster structure of the three-dimensional NCAs, the ternary metal sulfide electrode (Ni-Co-Fe-S@NCAs-NP) exhibits high specific capacitances (2159.7 F/g at 7 A/g and 1461 F/g at 35 A/g) with excellent rate capabilities.

We show how different algorithmic variations can be used to best effect depending upon the cluster structure of the graph being labelled and consider how features of the GPU architectures and host CPUs can be combined to best effect into a cluster component labelling algorithm for use in high performance simulations.

To evaluate the reliability and cluster structure of the Pediatric Quality of Life Inventory Type 1 Diabetes Module 3.0 (PedsQL-T1DM) and associated subscales and to explore the associations between PedsQL-T1DM total score and demographic and clinical characteristics and clinical indicators among a large racially/ethnically diverse cohort of youth with type 1 diabetes.

Intuitionally speaking, the cluster structures of data in feature spaces reflect the discriminative information of distinct classes.

Then, a set of Gaussian mixture models are used to capture the underlying cluster structures of the datasets.

The proposed CENI framework exactly tries to leverage the hidden cluster structures of nodes to improve the efficiency of the network inference process.

To overcome this problem, this paper proposes a two-step framework, Clustering Embedded Network Inference (CENI), which incorporates the cluster structures of nodes to improve the efficiency of existing network inference algorithm.

Therefore, four possible cluster structures of Zn2Si2, Zn3Si2, Zn4Si2, and Zn5Si2 (as shown in Fig. 3c) are constructed to be considered as this type of nanocluster in the FHUC.