A Visual Analytics Approach for Correlation, Classification, and Regression Analysis

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New approaches that combine the strengths of humans and machines are necessary to equip analysts with the proper tools for exploring today's increasing complex, multivariate data sets. In this paper, a novel visual data mining framework, called the Multidimensional Data eXplorer (MDX), is described that addresses the challenges of today's data by combining automated statistical analytics with a highly interactive parallel coordinates based canvas. In addition to several intuitive interaction capabilities, this framework offers a rich set of graphical statistical indicators, interactive regression analysis, visual correlation mining, automated axis arrangements and filtering, and data classification techniques. The current work provides ... continued below

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Steed, Chad A; SwanII, J. Edward; Fitzpatrick, Patrick J. & Jankun-Kelly, T.J. February 1, 2012.

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Description

New approaches that combine the strengths of humans and machines are necessary to equip analysts with the proper tools for exploring today's increasing complex, multivariate data sets. In this paper, a novel visual data mining framework, called the Multidimensional Data eXplorer (MDX), is described that addresses the challenges of today's data by combining automated statistical analytics with a highly interactive parallel coordinates based canvas. In addition to several intuitive interaction capabilities, this framework offers a rich set of graphical statistical indicators, interactive regression analysis, visual correlation mining, automated axis arrangements and filtering, and data classification techniques. The current work provides a detailed description of the system as well as a discussion of key design aspects and critical feedback from domain experts.

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  • Report No.: ORNL/TM-2012/68
  • Grant Number: DE-AC05-00OR22725
  • DOI: 10.2172/1035521 | External Link
  • Office of Scientific & Technical Information Report Number: 1035521
  • Archival Resource Key: ark:/67531/metadc845739

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  • February 1, 2012

Added to The UNT Digital Library

  • May 19, 2016, 3:16 p.m.

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  • Dec. 2, 2016, 6:14 p.m.

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Steed, Chad A; SwanII, J. Edward; Fitzpatrick, Patrick J. & Jankun-Kelly, T.J. A Visual Analytics Approach for Correlation, Classification, and Regression Analysis, report, February 1, 2012; United States. (digital.library.unt.edu/ark:/67531/metadc845739/: accessed September 26, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.