Resumen de Using Spatial Autocorrelation Measures for Data Clustering

Eduardo René Concepción Morales, Yosu Yurramendi Mendizabal

• 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.