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Visual data mining: integrating machine learning with information visualization.
| Content Provider | CiteSeerX |
|---|---|
| Author | Maniyar, Dharmesh M. Nabney, Ian T. |
| Abstract | Today, the data available to tackle many scientific challenges is vast in quantity and diverse in nature. The exploration of heterogeneous information spaces requires suitable mining algorithms as well as effective visual interfaces. Most existing systems concentrate either on mining algorithms or on visualization techniques. Though visual methods developed in information visualization have been helpful, for improved understanding of a complex large high-dimensional dataset, there is a need for an effective projection of such a dataset onto a lower-dimension (2D or 3D) manifold. This paper introduces a flexible visual data mining framework which combines advanced projection algorithms developed in the machine learning domain and visual techniques developed in the information visualization domain. The framework follows Shneiderman’s mantra to provide an effective user interface. The advantage of such an interface is that the user is directly involved in the data mining process. We integrate principled projection methods, such as Generative Topographic Mapping (GTM) and Hierarchical GTM (HGTM), with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates, billboarding, and user interaction facilities, to provide an integrated visual data mining framework. Results on a real life high-dimensional dataset from the chemoinformatics domain are also reported and discussed. Projection results of GTM are analytically compared with the projection results from other traditional projection methods, and it is also shown that the HGTM algorithm provides additional value for large datasets. The computational complexity of these algorithms is discussed to demonstrate their suitability for the visual data mining framework. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Information Visualization Visual Data Mining Integrating Machine Learning Projection Result Effective User Interface Visual Technique Visualization Technique Visual Data Mining Framework Shneiderman Mantra Improved Understanding Complex Large High-dimensional Dataset Many Scientific Challenge Additional Value Information Visualization Domain Magnification Factor Flexible Visual Data Mining Framework Powerful Visual Technique Effective Visual Interface Large Datasets Projection Algorithm Generative Topographic Mapping Integrated Visual Data Mining Framework Computational Complexity Hgtm Algorithm Parallel Coordinate Visual Method Chemoinformatics Domain Real Life High-dimensional Dataset Directional Curvature User Interaction Facility Effective Projection Projection Method Traditional Projection Method Hierarchical Gtm Data Mining Process Mining Algorithm Heterogeneous Information Space |
| Content Type | Text |
| Resource Type | Article |
