TY - GEN
T1 - An L∞ norm visual classifier
AU - Anand, Anushka
AU - Wilkinson, Leland
AU - Tuan, Dang Nhon
N1 - Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.
PY - 2009
Y1 - 2009
N2 - We introduce a mathematical framework, based on the L∞ norm distance metric, to describe human interactions in a visual data mining environment. We use the framework to build a classifier that involves an algebra on hyper-rectangles. Our classifier, called VisClassifier, generates set-wise rules from simple gestures in an exploratory visual GUI. Logging these rules allows us to apply our analysis to a new sample or batch of data so that we can assess the predictive power of our visualprocessing motivated classifier. The accuracy of this classifier on widely-used benchmark datasets rivals the accuracy of competitive classifiers.
AB - We introduce a mathematical framework, based on the L∞ norm distance metric, to describe human interactions in a visual data mining environment. We use the framework to build a classifier that involves an algebra on hyper-rectangles. Our classifier, called VisClassifier, generates set-wise rules from simple gestures in an exploratory visual GUI. Logging these rules allows us to apply our analysis to a new sample or batch of data so that we can assess the predictive power of our visualprocessing motivated classifier. The accuracy of this classifier on widely-used benchmark datasets rivals the accuracy of competitive classifiers.
KW - Supervised classification
KW - Visual data mining
UR - http://www.scopus.com/inward/record.url?scp=77951154863&partnerID=8YFLogxK
U2 - 10.1109/ICDM.2009.119
DO - 10.1109/ICDM.2009.119
M3 - Conference contribution
AN - SCOPUS:77951154863
SN - 9780769538952
T3 - Proceedings - IEEE International Conference on Data Mining, ICDM
SP - 687
EP - 692
BT - ICDM 2009 - The 9th IEEE International Conference on Data Mining
Y2 - 6 December 2009 through 9 December 2009
ER -