HD-Eye: visual mining of high-dimensional data

HD-Eye: Visual Mining of High-Dimensional Data

iconic visualizations of pro j e c t i o n s The large number of possible contracting pro j e c t i o n s demand a visualization te ch n i que for displaying th e main pro p e rties of the data dist ribution of as many projections as possible. Since we’re inte re sted in fi n d i n g 7 5 Examples of a projection and separator tree. Clockwise from the top: a projection and separator tree, iconic...

Mining High-Dimensional Data

With the rapid growth of computational biology and e-commerce applications, high-dimensional data becomes very common. Thus, mining highdimensional data is an urgent problem of great practical importance. However, there are some unique challenges for mining data of high dimensions, including (1) the curse of dimensionality and more crucial (2) the meaningfulness of the similarity measure in the...

Visual Interactive Neighborhood Mining on High Dimensional Data

Cluster analysis is widely used for explorative data analysis, however, it is not trivial to select the right method and optimal parameters. Moreover, not all clustering methods can work with raw or dirty data. In this paper, we introduce an interactive data exploration tool, VINeM, which combines interactive mining with unsupervised tools by exploiting an intuitive neighborhood-based visualiza...

CUDA-Accelerated HD-ODETLAP: Lossy High Dimensional Gridded Data Compression

We present High-dimensional Overdetermined Laplacian Partial Differential Equations (HD-ODETLAP), a high dimensional lossy compression algorithm and CUDA implementation that exploits data correlations across multiple dimensions of gridded GIS data. Exploiting the GPU gives a considerable speedup. In addition, HD-ODETLAP compresses much better than JPEG2000 and 3D-SPIHT, when fixing either the a...

Visualization & Data Mining for High Dimensional Datasets