Interactive Bivariate Mode Tree

被引:0
|
作者
Florek, Martin [1 ]
Hauser, Helwig [2 ]
机构
[1] Comenius Univ, Dept Appl Informat, Bratislava, Slovakia
[2] Univ Bergen, Dept Informat, Bergen, Norway
关键词
Mode Tree; Data Visualization; Kernel Density Estimation; GPU;
D O I
暂无
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Kernel density estimation (KDE) is widely used statistical method to study distribution of the data. The problem with this method is choosing the right bandwidth. In our work we focus on semiautomatic bandwidth selection with the use of visual paradigm of the Mode Tree. We not only enhanced the bivariate mode tree visualization, which was only sketched by the authors, but we also developed a hybrid CPU/GPU implementation to improve the speed of the mode tree construction.
引用
收藏
页码:41 / +
页数:2
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