dc.contributor.author | Pérez, D. | en_US |
dc.contributor.author | Zhang, L. | en_US |
dc.contributor.author | Schaefer, M. | en_US |
dc.contributor.author | Schreck, Tobias | en_US |
dc.contributor.author | Keim, D. | en_US |
dc.contributor.author | Díaz, I. | en_US |
dc.contributor.editor | M. Aupetit and L. van der Maaten | en_US |
dc.date.accessioned | 2014-02-01T15:50:31Z | |
dc.date.available | 2014-02-01T15:50:31Z | |
dc.date.issued | 2013 | en_US |
dc.identifier.isbn | 978-3-905674-53-8 | en_US |
dc.identifier.uri | http://dx.doi.org/10.2312/PE.VAMP.VAMP2013.021-025 | en_US |
dc.description.abstract | Projecting multidimensional data to a lower-dimensional visual display as a scatter-plot-like visualization is a common approach for analyzing multidimensional data. Many dimension reduction techniques exist for performing such a task, but the quality of projections varies in terms of both preserving the original data structure and avoiding cluttered visual displays. In this paper, we propose an interactive feature transformation approach that allows the analyst to monitor and improve the projection quality by transforming feature space and assessing/ comparing the quality of different projection results. The method integrates feature selection and transformation as well as a variety of projection quality measures to help analyst generate uncluttered projections that preserve the structural properties of the data. These projections enhance the visual analysis process and provide a better understanding of data. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.subject | I.5.2 [Pattern Recognition] | en_US |
dc.subject | Design Methodology | en_US |
dc.subject | Feature evaluation and selection | en_US |
dc.subject | Pattern analysis | en_US |
dc.title | Interactive Visualization and Feature Transformation for Multidimensional Data Projection | en_US |
dc.description.seriesinformation | EuroVis Workshop on Visual Analytics using Multidimensional Projections | en_US |