Visual data mining using principled projection algorithms and information visualization techniques

Dharmesh M. Maniyar, Ian T. Nabney

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

We introduce a flexible visual data mining framework which combines advanced projection algorithms from the machine learning domain and visual techniques developed in the information visualization domain. The advantage of such an interface is that the user is directly involved in the data mining process. We integrate principled projection algorithms, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates and billboarding, to provide a visual data mining framework. Results on a real-life chemoinformatics dataset using GTM are promising and have been analytically compared with the results from the traditional projection methods. 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. Copyright 2006 ACM.

Original languageEnglish
Title of host publicationProceedings of the Twelfth ACM SIGKDD international conference on knowledge discovery and data mining
Place of PublicationNew York (US)
PublisherACM
Pages643-648
Number of pages6
Volume2006
ISBN (Print)1-59593-339-5
DOIs
Publication statusPublished - 16 Oct 2006
Event12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - Philadelphia, United States
Duration: 20 Aug 200623 Aug 2006

Conference

Conference12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Abbreviated titleKDD '06
CountryUnited States
CityPhiladelphia
Period20/08/0623/08/06

Fingerprint

Data mining
Visualization
Learning systems
Computational complexity

Keywords

  • visual data mining
  • probabilistic projection algorithms
  • information visualization techniques

Cite this

Maniyar, D. M., & Nabney, I. T. (2006). Visual data mining using principled projection algorithms and information visualization techniques. In Proceedings of the Twelfth ACM SIGKDD international conference on knowledge discovery and data mining (Vol. 2006, pp. 643-648). New York (US): ACM. https://doi.org/10.1145/1150402.1150481
Maniyar, Dharmesh M. ; Nabney, Ian T. / Visual data mining using principled projection algorithms and information visualization techniques. Proceedings of the Twelfth ACM SIGKDD international conference on knowledge discovery and data mining. Vol. 2006 New York (US) : ACM, 2006. pp. 643-648
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Maniyar, DM & Nabney, IT 2006, Visual data mining using principled projection algorithms and information visualization techniques. in Proceedings of the Twelfth ACM SIGKDD international conference on knowledge discovery and data mining. vol. 2006, ACM, New York (US), pp. 643-648, 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Philadelphia, United States, 20/08/06. https://doi.org/10.1145/1150402.1150481

Visual data mining using principled projection algorithms and information visualization techniques. / Maniyar, Dharmesh M.; Nabney, Ian T.

Proceedings of the Twelfth ACM SIGKDD international conference on knowledge discovery and data mining. Vol. 2006 New York (US) : ACM, 2006. p. 643-648.

Research output: Chapter in Book/Report/Conference proceedingChapter

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Maniyar DM, Nabney IT. Visual data mining using principled projection algorithms and information visualization techniques. In Proceedings of the Twelfth ACM SIGKDD international conference on knowledge discovery and data mining. Vol. 2006. New York (US): ACM. 2006. p. 643-648 https://doi.org/10.1145/1150402.1150481