Sentence examples for multivariate network from inspiring English sources

In this paper, we propose TMNVis, an interactive visualization system to explore the evolution of temporal multivariate network.

In 16 healthy participants, we estimated the univariate properties of the BOLD signal, as well as a bivariate measure of functional connectivity and multivariate network topology measures.

Finally, NMI is a scalar measure of global (rather than pairwise) mutual information in a multivariate network, and hence relies on less assumptions for cross-network comparisons than historical approaches.

The present study examines the application of Normalized Multiinformation (NMI) as a scalar measure of shared information content in a multivariate network that is robust with respect to changes in network size.

A similar multivariate network analysis using a modified form of principal component analysis, the Scaled Subprofile Model (SSM), was applied by Smith et al. to single-subject fMRI data to verify the neural network associated with an anatomically well-characterized simple motor task [ 20].

Temporal (Dynamic) multivariate networks consist of objects and relationships with a variety of attributes, and the networks change over time.

However, this limitation became less important, as we used a technique with increased sensitivity and we focused on a multivariate networks analysis prospective.

The major differences between the different studies lie in the exact classification algorithm, even though some popular classifiers (K-nearest neighbour, Gaussian multivariate, neural network) are often used as a basis.

Among other tools (such as multivariate analysis), network theory is proving extremely helpful in this task, as it provides a theoretical framework and useful analytical methods to assess patterns of interaction among several species of frugivores and fruits [5].

Many uncharacterized proteins were identified by multivariate correlation network analysis to be involved in the response to N starvation.

We therefore used a multivariate Bayesian Network analysis (BN) and compiled all patient information significantly associated with disease progression groups in the univariate analysis.