A Novel Triangulate Mapping Based on Self- Organized Anchor Points for Data Visualization

Yii, Ming Leong and Teh, Chee Siong (2017) A Novel Triangulate Mapping Based on Self- Organized Anchor Points for Data Visualization. Advance Science Letters, 23 (11). pp. 11083-11087. ISSN 1936-6612

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Abstract

Without a form of visual feedback, multivariate data would be reduced to a lump of numbers that very few people would be able to appreciate and be benefited from. This research paper proposes a novel triangulate mapping technique based on selforganizing anchor points for multivariate data visualization. Self-Organizing Map (SOM) and a modified Adaptive Coordinates (AC) are hybridized to produce the anchor points in the 2D space. The trained anchor points are used to triangulate data onto a topologically preserved 2D space. The empirical studies that produce topologically preserved data visualizations for high dimension and arbitrarily shaped clusters in simulated, benchmarking, and real-life dataset show its usefulness in providing intuitive visual feedback to the user.

Item Type: Article
Uncontrolled Keywords: Triangulate mapping, self-organizing map, topologically preserved visualization, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Academic Faculties, Institutes and Centres > Faculty of Cognitive Sciences and Human Development
Depositing User: Siong
Date Deposited: 12 Dec 2017 02:05
Last Modified: 12 Dec 2017 02:05
URI: http://ir.unimas.my/id/eprint/18827

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