An L∞ Norm Visual Classifier

被引:9
作者
Anand, Anushka [1 ]
Wilkinson, Leland [2 ]
Dang Nhon Tuan [1 ]
机构
[1] Univ Illinois, Chicago, IL 60607 USA
[2] SYSTAT Inc, Chicago, IL USA
来源
2009 9TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING | 2009年
基金
中国国家自然科学基金;
关键词
Visual data mining; Supervised classification;
D O I
10.1109/ICDM.2009.119
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We introduce a mathematical framework, based on the L-infinity 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 visual-processing motivated classifier. The accuracy of this classifier on widely-used benchmark datasets rivals the accuracy of competitive classifiers.
引用
收藏
页码:687 / +
页数:2
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