A visual analytics approach for correlation, classification, and regression analysis

Chad A. Steed, J. Edward Swan, Patrick J. Fitzpatrick, T. J. Jankun-Kelly

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations

Abstract

New approaches that combine the strengths of humans and machines are necessary to equip analysts with the proper tools for exploring today's increasingly complex, multivariate data sets. In this chapter, a 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. This chapter provides a detailed description of the system as well as a discussion of key design aspects and critical feedback from domain experts.

Original languageEnglish
Title of host publicationInnovative Approaches of Data Visualization and Visual Analytics
PublisherIGI Global
Pages25-44
Number of pages20
ISBN (Electronic)9781466643109
ISBN (Print)9781466643093
DOIs
StatePublished - Jul 31 2013

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