Sentence examples for data transformation of from inspiring English sources

In this case, however, the B implementation of each module was available as reference for the refinement of the test data (transformation of abstract to concrete data).

This includes the removal of "error" data points and dehydration stage from original TGA data, transformation of TGA data to conversion data, differentiation of conversion data and smoothing of derivative conversion data, interpolation of conversion and derivative conversion data, isoconversional calculations, and reconstruction of kinetic process.

Data transformation of the cumulative response variable (natural log or square root) was applied to meet the assumptions of parametric testing, where applicable.

Remarkably, data transformation of the highly noisy expression data successfully led to lower the coefficient of variation (CV) for the within-class samples as well as improved the correlation with tissue phenotypes.

In addition, to provide for backward compatibility of previously mapped data (output in 'collated' format), and to assist in tertiary analysis, we have included a Java utility for data transformation of colour-space mapped data into Sequence Alignment/Map (SAM) format.

Effect of data transformation on the classification ability of neural network is studied by varying the size of array and corrupting the data with synthetic noise.

In addition, the effects of data transformation on model performance were also investigated.

Additional file 1: Additional information and calculations on health care sectors and associated National Health Expenditure categories; results of data transformations of BIR in physician offices; and sensitivity analysis findings on total and added BIR.

The Web services are then able to manage declarative transaction and complete the object of Internet data transformation for provision of the Web application context.

PCA is an unsupervised data transformation procedure of complex data sets.

"We're dealing with the manipulation of data, the transformation of data, and the preparation of data for analytics," says Mor. "This is to get data from a variety of data stores: get it, normalize it, clean it, and put that into your analytic data store of choice".