Using Spatial Autocorrelation Measures for Data Clustering

  1. Concepción Morales, Eduardo René
  2. Yurramendi Mendizabal, Yosu
Libro:
XII Conferencia de la Asociación Española para la Inteligencia Artificial: (CAEPIA 2007). Actas
  1. Borrajo Millán, Daniel (coord.)
  2. Castillo Vidal, Luis (coord.)
  3. Corchado Rodríguez, Juan Manuel (coord.)

Editorial: Universidad de Salamanca

ISBN: 978-84-611-8846-8,  978-84-611-8848-2

Año de publicación: 2007

Volumen: 2

Páginas: 1-9

Congreso: Conferencia de la Asociación Española para la Inteligencia Artificial (12. 2007. Salamanca)

Tipo: Aportación congreso

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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.

Fuente de los datos: Dialnet