A Pareto Self-Organizing Map

Hunter, Andrew and Kennedy, Richard Lee (2002) A Pareto Self-Organizing Map. In: International Conference on Artificial Neural Networks, 27-30 August 2002, Madrid, Spain.

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A Pareto Self-Organizing Map
This paper introduces the concept of a Pareto SOFM.
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Abstract

Abstract. Self Organizing Features Maps are used for a variety of tasks in visualization and clustering, acting to transform data from a highdimensional original feature space to a (usually) two-dimensional grid.
SOFMs use a similarity metric in the input space, and this composes individual feature differences in a way that is not always desirable. This paper introduces the concept of a Pareto SOFM, which partitions features into groups, defines separate metrics in each partition, and retrieves
a set of prototypes that trade off matches in different partitions. It is suitable for a wide range of exploratory tasks, including visualization and clustering. . . .

Item Type:Conference or Workshop Item (Paper)
Additional Information:Abstract. Self Organizing Features Maps are used for a variety of tasks in visualization and clustering, acting to transform data from a highdimensional original feature space to a (usually) two-dimensional grid. SOFMs use a similarity metric in the input space, and this composes individual feature differences in a way that is not always desirable. This paper introduces the concept of a Pareto SOFM, which partitions features into groups, defines separate metrics in each partition, and retrieves a set of prototypes that trade off matches in different partitions. It is suitable for a wide range of exploratory tasks, including visualization and clustering. . . .
Keywords:Self-Organising Map, Neural networks, Pareto, SOFM
Subjects:G Mathematical and Computer Sciences > G730 Neural Computing
Divisions:College of Science > School of Computer Science
ID Code:1893
Deposited By: Tammie Farley
Deposited On:30 Jun 2009 15:45
Last Modified:13 Mar 2013 08:32

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