@COMMENT This file was generated by bib2html.pl version 0.94
@COMMENT written by Patrick Riley
@TechReport{TR12-vaa,
author = {Chad A. Steed and J. Edward {Swan~II} and Patrick J. Fitzpatrick
and T.J. Jankun-Kelly},
title = {A Visual Analytics Approach for Correlation, Classification, and
Regression Analysis},
institution = {Oak Ridge National Laboratory, Oak Ridge, TN, USA},
type = {Technical Report},
number = {ORNL/TM-2012/68},
date = {February 21},
month = {February},
year = 2012,
abstract = {
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
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.
},
}