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

Steed, C., Swan II, J. E., Fitzpatrick, P. J., & Jankun-Kelly, T. J. (2014). A Visual Analytics Approach for Correlation, Classification, and Regression Analysis. In Mao Lin Huang and Weidong Huang (Eds.), Innovative approaches of data visualization and visual analytics. IGI Global. 25-45. DOI:10.4018/978-1-4666-4309-3.

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.