While the scope of visual analytics is broad, one principle that has emerged over the years is the need for visual analytics systems to leverage computational methods in statistics, data mining, knowledge discovery, and machine learning for large-scale data analysis.
In these systems, the human operator works alongside the computational processes in an integrated fashion—the computer can sift through large amounts of data and identify the relevant information, while the human interactively explores the reduced data space to discover trends and patterns and make informed decisions.
The two components operate in coordination, allowing for a continuous and cooperative analytical loop.
While the scope of visual analytics is broad, one principle that has emerged over the years is the need for visual analytics systems to leverage computational methods in statistics, data mining, knowledge discovery, and machine learning for large-scale data analysis. In these systems, the human operator works alongside the computational processes in an integrated fashion—the computer can sift through large amounts of data and identify the relevant information, while the human interactively explores the reduced data space to discover trends and patterns and make informed decisions. The two components operate in coordination, allowing for a continuous and cooperative analytical loop.
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