Sentence examples for importance for the data from inspiring English sources

Of particular importance for the data set analysis is the opportunity to perform graphical analysis of the data set or subset.

Since Bayesian logistic regression is well suited for quantifying the relative importance of the data features and therefore facilitated interpretation of the obtained importance maps [30], it was the method of choice for the analysis.

Encounters as such are characterized by reason for encounter, diagnosis (corresponds to AsessmentResult) and procedure (corresponds to intervention).> On the other hand, several concepts of the workflow description are only part of a data model and have little importance for the information model (e.g. data check, database controller, data controller, EHR, genetic database, care database).

For uncentered and centered data, both before and after the transformations, they are identical for the MODIS data sets (991.80 and 1058.76 in Table 2) and practically of equal importance for the Landsat5 TM data sets (64.97 and 55.13 in Table 2 and 67.35, 66.23 and 54.69, 54.62 in Table 4).

The resulting posterior MIPs are interpreted as follows: high (close to 1) for classes of effect deemed essential to the model fit, low (near 0) for those with apparently negligible effects, and in the middle (∼0.5) for those whose importance, given the data collected so far, remains uncertain (more guidelines for interpretation in Statistical Models and Methods).

The synthesis technique and knowledge about structure and chemical composition of these FeNi nanoparticles is of particular importance for the design of miniaturized data recording and data probe devices.

The importance for omics data integration in understanding biology has been demonstrated by studies with multidimensional datasets at the DNA, RNA and protein levels.

A large amount of literature on thermogravimetric analyzer determined char gasification kinetics is examined and the importance of chemisorption dynamics for the data assessed.

The identification and modeling of the various leakage components in DRAM cell transistors with three-dimensional structures is of great importance for the estimation of their data retention characteristics.

It highlights the importance for the use of expression data.

The identification of the spatial relationships among neighbors is also of great importance for the last step of data analysis; modeling and hypothesis testing.