A New Method for Emulating Self-Organizing Maps for Visualization of Datasets

Author:

Cordel Macario O.1,Azcarraga Arnulfo P.1

Affiliation:

1. College of Computer Studies, De La Salle University, 2401 Taft Avenue, Malate, Manila, Philippines

Abstract

Several time-critical problems relying on large amount of data, e.g., business trends, disaster response and disease outbreak, require cost-effective, timely and accurate data summary and visualization, in order to come up with an efficient and effective decision. Self-organizing map (SOM) is a very effective data clustering and visualization tool as it provides intuitive display of data in lower-dimensional space. However, with [Formula: see text] complexity, SOM becomes inappropriate for large datasets. In this paper, we propose a force-directed visualization method that emulates SOMs capability to display the data clusters with [Formula: see text] complexity. The main idea is to perform a force-directed fine-tuning of the 2D representation of data. To demonstrate the efficiency and the vast potential of the proposed method as a fast visualization tool, the methodology is used to do a 2D-projection of the MNIST handwritten digits dataset.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computer Science Applications,Theoretical Computer Science,Software

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