Beyond K-means: Clusters Identification for GIS

作者: Andreas Hamfelt , Mikael Karlsson , Tomas Thierfelder , Vladislav Valkovsky

DOI: 10.1007/978-3-642-19766-6_8

关键词:

摘要: Clustering is an important concept for analysis of data in GIS. Due to the potentially large amount of data in such systems, the time complexity for clustering algorithms is critical. K …

参考文章(33)
Richard C. Dubes, Cluster analysis and related issues Handbook of pattern recognition & computer vision. pp. 3- 32 ,(1993)
Warren S. Sarle, Cubic Clustering Criterion SAS Institute. ,(1983)
C. H. Chen, P. S. P. Wang, L. F. Pau, Handbook of Pattern Recognition and Computer Vision ,(1993)
David G. Stork, Richard O. Duda, Peter E. Hart, Pattern Classification (2nd ed.) ,(1999)
Vipin Kumar, Pang-Ning Tan, Michael M. Steinbach, Introduction to Data Mining ,(2013)
Larry Wasserman, All of Nonparametric Statistics ,(2008)
Usama M. Fayyad, Paul S. Bradley, Refining Initial Points for K-Means Clustering international conference on machine learning. pp. 91- 99 ,(1998)
Philipp Galjano, Vasily Popovich, None, Intelligent Images Analysis in GIS IF&GIS. pp. 45- 68 ,(2007) , 10.1007/978-3-540-37629-3_4