Sentence examples for types of data representation from inspiring English sources
Common types of data representation are illustrated.
For the smaller confirmatory bioassay datasets, two types of data representation are used in order to see if adding more information improves the classification results.
The aim of these investigations was to detect relationships among different types of data representation, correct interpretation of data, and personal preferences.
Considering various types of data representation and processing, it has been decided to keep whole 3D information, although for a purpose of analysis of single, directional point cloud the range image representation would suffice.
It has been recognized that gene regulatory network inference (GRNI) algorithms are an important means to obtain genome-scale causal interaction networks which seem more amenable for a functional interpretation than other types of data representations [ 2].
Some of the advantages of learned abstract representations by Deep Learning include, a simple model can work effectively with the knowledge of more abstract data representation, automation of data representation extraction can lead to a broad application to different data types.
In general, NSS have incorporated the following types of information representation for quantitative data: (1) solely text-based systems, (2) numerical systems offering analytical decision support with utility functions and preference values, (3) systems offering stylized decision aids in the form of tables, and (4) systems offering graphical display of the negotiation history.
The main advantage of these solutions is to offer powerful visualization with numerous types of graph for data representation and allow high interactivity with these data for changing parameters or zooming.
This variation detection task is further complicated by the different types of errors and data representation methods used by various technologies.
Algorithms can be implemented for classes of pixel types and generic access patterns by which they become independent of the specific dimensionality, pixel type and data representation.
This conversion creates two types of data: pathway topology and its graphical representations.
