Sentence examples for multivariate representation from inspiring English sources

Multivariate representation like that in fig.13 for Carcer and fig.14 for Tullianum was calculated for each measurement point and also the class distribution was draft.

The strong discriminative power of the consensus signature by a multivariate representation of the 11 probesets is shown in Figure 8.

The strong discriminative power of the selected probe-sets is depicted by either a heat-map plot or a multivariate representation.

The use of linear combinations also aids in procuring a multivariate representation of the quality information that may, under a null hypothesis of equivalent quality, be reasonably approximated by a multivariate Gaussian probability model.

Second, we evaluate the effectiveness of the proposed technique in a controlled user study, comparing it to the two other common multivariate representations of clusters: parallel coordinates and scatter plot matrices.

The POD employed herein is a specific POD for arbitrary multivariate data representation.

Also, it is assumed that the multivariate molecular representation of the set of compounds reveals these analogies, i.e. physical and chemical properties of a chemical substance can be computed from its molecular structure, encoded in a numerical form with the aid of various descriptors.

This step pursues parsimonious integration of the various metrics and yields a multivariate quality representation that should be reasonably approximated by the multivariate Gaussian model.

Categorical Bayesian networks mitigate some of these problems by providing noise and bias reduction through discretization, ability to handle non-linear gene interaction effects and efficient multivariate model representation.

In this form, the relationship among the gene expression is summarized (1) across all microarrays (i.e., it is a multivariate statistical representation, involving the entire matrix Y, rather than a single column), and (2) at the level of the joint marginal distribution within each microarray (i.e., it involves the full columns in Y, rather than just their individual elements).

To find time instants of changing correlation directions, key turning points (KTPs) are determined by a piecewise linear representation of multivariate time series.