Using Spatial Autocorrelation Measures for Data Clustering

• Autores: Eduardo René Concepción Morales, Yosu Yurramendi Mendizabal
• Localización: XII Conferencia de la Asociación Española para la Inteligencia Artificial: (CAEPIA 2007). Actas / coord. por Daniel Borrajo Millán, Luis Castillo Vidal, Juan Manuel Corchado Rodríguez, Vol. 2, 2007, ISBN 978-84-611-8848-2, págs. 1-9
• Idioma: inglés
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• Resumen

  • Unsupervised classification or clustering has been used in many disciplines and contexts. Traditional methodologies are mostly based on the minimization of the distance between data and the cluster means without considering any other possible relationship present in data, e.g. spatial interactions. We propose a clustering evaluation function based on a measure of spatial autocorrelation and show its application to clustering. We provide some examples of the quality of the proposed criterion.