Data Clustering Based on Energy Exchange Dynamics

• Roberto Alves Gueleri USP
• Zhao Liang USP

Abstract

We present a data clustering method based on dynamics of energy exchange. Initially, each object is assigned an energy state. So the process consists of the progressive exchange of energy among objects. When two of them reach close enough energy states, they are grouped together. The distance between each pair of objects defines its degree of interaction. Thus, it tends to gradually cluster the regions of higher density of objects. The natural and dynamic property of the proposed method shows interesting results. Simulations with artificial and real data show its potentialities and limitations.

References

Uci machine learning repository. Dispońıvel em [link]. Acessado em maio de 2011.

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