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Volumn 104, Issue 6, 2014, Pages 1134-1156

Spatial Clustering Overview and Comparison: Accuracy, Sensitivity, and Computational Expense

Author keywords

cluster analysis; hot spots; knowledge discovery; method selection; scale

Indexed keywords

ACCURACY ASSESSMENT; CLUSTER ANALYSIS; KNOWLEDGE; NUMERICAL MODEL; PERFORMANCE ASSESSMENT; SPATIAL ANALYSIS;

EID: 84908220528     PISSN: 00045608     EISSN: 14678306     Source Type: Journal    
DOI: 10.1080/00045608.2014.958389     Document Type: Article
Times cited : (101)

References (74)
  • 2
    • 33748616521 scopus 로고    scopus 로고
    • Using AMOEBA to create a spatial weights matrix and identify spatial clusters
    • Aldstadt, J., and A. Getis. 2006. Using AMOEBA to create a spatial weights matrix and identify spatial clusters. Geographical Analysis 38 (4): 327–43.
    • (2006) Geographical Analysis , vol.38 , Issue.4 , pp. 327-343
    • Aldstadt, J.1    Getis, A.2
  • 3
    • 0029507498 scopus 로고
    • Local indicators of spatial association—LISA
    • Anselin, L. 1995. Local indicators of spatial association—LISA. Geographical Analysis 27 (2): 93–115.
    • (1995) Geographical Analysis , vol.27 , Issue.2 , pp. 93-115
    • Anselin, L.1
  • 4
    • 84908182321 scopus 로고    scopus 로고
    • Anselin, L., A. T. Murray, and S. Rey. 2013. 8 spatial analysis. In The Oxford handbook of quantitative methods: Vol. 2. Statistical analysis, ed. T. Little, 154. Oxford, UK: Oxford University Press.
  • 7
    • 84908182320 scopus 로고    scopus 로고
    • Block, C. R. 1995. STAC hot-spot areas: A statistical tool for law enforcement decisions. In Crime analysis through computer mapping, ed. C. R. Block, M. Dabdoub, and S. Fregly, 15–32. Washington, DC: Police Executive Research Forum.
  • 8
    • 0031191630 scopus 로고    scopus 로고
    • Bradley, A. P. 1997. The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognition 30 (7): 1145–59.
  • 9
    • 0030432956 scopus 로고    scopus 로고
    • Geographically weighted regression: A method for exploring spatial nonstationarity
    • Brunsdon, C., A. S. Fotheringham, and M. E. Charlton. 1996. Geographically weighted regression: A method for exploring spatial nonstationarity. Geographical Analysis 28 (4): 281–98.
    • (1996) Geographical Analysis , vol.28 , Issue.4 , pp. 281-298
    • Brunsdon, C.1    Fotheringham, A.S.2    Charlton, M.E.3
  • 10
    • 33644933129 scopus 로고    scopus 로고
    • Controlling the false discovery rate: A new application to account for multiple and dependent tests in local statistics of spatial association
    • Caldas de Castro, M., and B. H. Singer. 2006. Controlling the false discovery rate: A new application to account for multiple and dependent tests in local statistics of spatial association. Geographical Analysis 38 (2): 180–208.
    • (2006) Geographical Analysis , vol.38 , Issue.2 , pp. 180-208
    • Caldas de Castro, M.1    Singer, B.H.2
  • 11
    • 77958522661 scopus 로고    scopus 로고
    • Canc˛ado, A. L., A. R. Duarte, L. Duczmal, S. J. Ferreira, C. M. Fonseca, and E. C. D. M. Gontijo. 2010. Penalized likelihood and multi-objective spatial scans for the detection and inference of irregular clusters. International Journal of Health Geographics 9 (1): 55.
  • 12
    • 84908182317 scopus 로고    scopus 로고
    • Cliff, A. D., and J. K. Ord. 1981. Spatial processes: Models & applications (Vol. 44). London: Pion.
  • 13
    • 22444447333 scopus 로고    scopus 로고
    • A genetic approach to detecting clusters in point data sets
    • Conley, J., M. Gahegan, and J. Macgill. 2005. A genetic approach to detecting clusters in point data sets. Geographical Analysis 37 (3): 286–314.
    • (2005) Geographical Analysis , vol.37 , Issue.3 , pp. 286-314
    • Conley, J.1    Gahegan, M.2    Macgill, J.3
  • 14
    • 0034019401 scopus 로고    scopus 로고
    • A comparative evaluation of approaches to urban crime pattern analysis
    • Craglia, M., R. Haining, and P. Wiles. 2000. A comparative evaluation of approaches to urban crime pattern analysis. Urban Studies 37 (4): 711–29.
    • (2000) Urban Studies , vol.37 , Issue.4 , pp. 711-729
    • Craglia, M.1    Haining, R.2    Wiles, P.3
  • 16
    • 0037273544 scopus 로고    scopus 로고
    • Cluster analysis of gene expression data
    • Domany, E. 2003. Cluster analysis of gene expression data. Journal of Statistical Physics 110 (3–6): 1117–39.
    • (2003) Journal of Statistical Physics , vol.110 , Issue.3-6 , pp. 1117-1139
    • Domany, E.1
  • 17
    • 1142280371 scopus 로고    scopus 로고
    • A simulated annealing strategy for the detection of arbitrarily shaped spatial clusters
    • Duczmal, L., and R. Assuncao. 2004. A simulated annealing strategy for the detection of arbitrarily shaped spatial clusters. Computational Statistics & Data Analysis 45 (2): 269–86.
    • (2004) Computational Statistics & Data Analysis , vol.45 , Issue.2 , pp. 269-286
    • Duczmal, L.1    Assuncao, R.2
  • 24
    • 33646023117 scopus 로고    scopus 로고
    • An introduction to ROC analysis
    • Fawcett, T. 2006. An introduction to ROC analysis. Pattern Recognition Letters 27 (8): 861–74.
    • (2006) Pattern Recognition Letters , vol.27 , Issue.8 , pp. 861-874
    • Fawcett, T.1
  • 26
    • 0030432710 scopus 로고    scopus 로고
    • A comparison of three exploratory methods for cluster detection in spatial point patterns
    • Fotheringham, A. S., and F. B. Zhan. 1996. A comparison of three exploratory methods for cluster detection in spatial point patterns. Geographical Analysis 28 (3): 200–18.
    • (1996) Geographical Analysis , vol.28 , Issue.3 , pp. 200-218
    • Fotheringham, A.S.1    Zhan, F.B.2
  • 27
    • 10044260670 scopus 로고    scopus 로고
    • Likelihood-based tests for localized spatial clustering of disease
    • Gangnon, R. E., and M. K. Clayton. 2004. Likelihood-based tests for localized spatial clustering of disease. Environmetrics 15 (8): 797–810.
    • (2004) Environmetrics , vol.15 , Issue.8 , pp. 797-810
    • Gangnon, R.E.1    Clayton, M.K.2
  • 28
    • 0346216900 scopus 로고    scopus 로고
    • A novel genetic algorithm for automatic clustering
    • Garai, G., and B. B. Chaudhuri. 2004. A novel genetic algorithm for automatic clustering. Pattern Recognition Letters 25 (2): 173–87.
    • (2004) Pattern Recognition Letters , vol.25 , Issue.2 , pp. 173-187
    • Garai, G.1    Chaudhuri, B.B.2
  • 29
    • 84977363017 scopus 로고
    • The analysis of spatial association by use of distance statistics
    • Getis, A., and J. K. Ord. 1992. The analysis of spatial association by use of distance statistics. Geographical Analysis 24 (3): 189–206.
    • (1992) Geographical Analysis , vol.24 , Issue.3 , pp. 189-206
    • Getis, A.1    Ord, J.K.2
  • 30
    • 13144297785 scopus 로고    scopus 로고
    • Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: The case of lung cancer in Long Island, New York
    • Goovaerts, P., and G. Jacquez. 2004. Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: The case of lung cancer in Long Island, New York. International Journal of Health Geographics 3 (1): 14.
    • (2004) International Journal of Health Geographics , vol.3 , Issue.1 , pp. 14
    • Goovaerts, P.1    Jacquez, G.2
  • 31
    • 33646398863 scopus 로고    scopus 로고
    • On the application of fuzzy clustering for crime hot spot detection
    • Grubesic, T. H. 2006. On the application of fuzzy clustering for crime hot spot detection. Journal of Quantitative Criminology 22 (1): 77–105.
    • (2006) Journal of Quantitative Criminology , vol.22 , Issue.1 , pp. 77-105
    • Grubesic, T.H.1
  • 32
    • 0036304306 scopus 로고    scopus 로고
    • Alcohol mortality: A comparison of spatial clustering methods
    • Hanson, C. E., and W. F. Wieczorek. 2002. Alcohol mortality: A comparison of spatial clustering methods. Social Science & Medicine 55 (5): 791–802.
    • (2002) Social Science & Medicine , vol.55 , Issue.5 , pp. 791-802
    • Hanson, C.E.1    Wieczorek, W.F.2
  • 34
    • 60249090294 scopus 로고    scopus 로고
    • Evaluating spatial methods for investigating global clustering and cluster detection of cancer cases
    • Huang, L., L. W. Pickle, and B. Das. 2008. Evaluating spatial methods for investigating global clustering and cluster detection of cancer cases. Statistics in Medicine 27 (25): 5111–42.
    • (2008) Statistics in Medicine , vol.27 , Issue.25 , pp. 5111-5142
    • Huang, L.1    Pickle, L.W.2    Das, B.3
  • 37
    • 33746257145 scopus 로고    scopus 로고
    • The practice of cluster analysis
    • Kettenring, J. R. 2006. The practice of cluster analysis. Journal of Classification 23 (1): 3–30.
    • (2006) Journal of Classification , vol.23 , Issue.1 , pp. 3-30
    • Kettenring, J.R.1
  • 38
    • 84989737730 scopus 로고
    • Optimal clustering: A model and method
    • Klein, G., and J. E. Aronson. 1991. Optimal clustering: A model and method. Naval Research Logistics (NRL) 38 (3): 447–61.
    • (1991) Naval Research Logistics (NRL) , vol.38 , Issue.3 , pp. 447-461
    • Klein, G.1    Aronson, J.E.2
  • 39
    • 0016784903 scopus 로고
    • 391: A Monte Carlo comparison of six clustering procedures
    • Kuiper, F. K., and L. Fisher. 1975. 391: A Monte Carlo comparison of six clustering procedures. Biometrics 31:777–83.
    • (1975) Biometrics , vol.31 , pp. 777-783
    • Kuiper, F.K.1    Fisher, L.2
  • 41
    • 0029055093 scopus 로고
    • Spatial disease clusters: Detection and inference
    • Kulldorff, M., and N. Nagarwalla. 1995. Spatial disease clusters: Detection and inference. Statistics in Medicine 14 (8): 799–810.
    • (1995) Statistics in Medicine , vol.14 , Issue.8 , pp. 799-810
    • Kulldorff, M.1    Nagarwalla, N.2
  • 43
    • 0024937968 scopus 로고
    • Spatial pattern and ecological analysis
    • Legendre, P., and M. J. Fortin. 1989. Spatial pattern and ecological analysis. Vegetatio 80 (2): 107–38.
    • (1989) Vegetatio , vol.80 , Issue.2 , pp. 107-138
    • Legendre, P.1    Fortin, M.J.2
  • 46
    • 0000176022 scopus 로고    scopus 로고
    • Spatial analysis using clustering methods: Evaluating central point and median approaches
    • Murray, A. T. 1999. Spatial analysis using clustering methods: Evaluating central point and median approaches. Journal of Geographical Systems 1 (4): 367–83.
    • (1999) Journal of Geographical Systems , vol.1 , Issue.4 , pp. 367-383
    • Murray, A.T.1
  • 47
    • 0034093011 scopus 로고    scopus 로고
    • Spatial characteristics and comparisons of interaction and median clustering models
    • ———. 2000. Spatial characteristics and comparisons of interaction and median clustering models. Geographical Analysis 32 (1): 1–18.
    • (2000) Geographical Analysis , vol.32 , Issue.1 , pp. 1-18
  • 50
    • 84935126996 scopus 로고    scopus 로고
    • Exploring spatial patterns of crime using non-hierarchical cluster analysis
    • Berlin: Springer
    • ———. 2013. Exploring spatial patterns of crime using non-hierarchical cluster analysis. In Crime modeling and mapping using geospatial technologies, ed. M. Leitner, 105–24. Berlin: Springer.
    • (2013) Crime modeling and mapping using geospatial technologies
    • Leitner, M.1
  • 51
    • 84920133396 scopus 로고    scopus 로고
    • Spatially significant cluster detection
    • Murray, A. T., T. H. Grubesic, and R. Wei. 2013. Spatially significant cluster detection. Spatial Statistics. http://dx.doi.org/10.1016/j.spasta.2014.03.001
    • (2013) Spatial Statistics
    • Murray, A.T.1    Grubesic, T.H.2    Wei, R.3
  • 52
    • 0035610888 scopus 로고    scopus 로고
    • Exploratory spatial data analysis techniques for examining urban crime implications for evaluating treatment
    • Murray, A. T., I. McGuffog, J. S. Western, and P. Mullins. 2001. Exploratory spatial data analysis techniques for examining urban crime implications for evaluating treatment. British Journal of Criminology 41 (2): 309–29.
    • (2001) British Journal of Criminology , vol.41 , Issue.2 , pp. 309-329
    • Murray, A.T.1    McGuffog, I.2    Western, J.S.3    Mullins, P.4
  • 53
    • 0005852342 scopus 로고
    • A geostatistical basis for spatial weighting in multivariate classification
    • Oliver, M. A., and R. Webster. 1989. A geostatistical basis for spatial weighting in multivariate classification. Mathematical Geology 21 (1): 15–35.
    • (1989) Mathematical Geology , vol.21 , Issue.1 , pp. 15-35
    • Oliver, M.A.1    Webster, R.2
  • 55
    • 0029514351 scopus 로고
    • Local spatial autocorrelation statistics: Distributional issues and an application
    • Ord, J. K., and A. Getis. 1995. Local spatial autocorrelation statistics: Distributional issues and an application. Geographical Analysis 27 (4): 286–306.
    • (1995) Geographical Analysis , vol.27 , Issue.4 , pp. 286-306
    • Ord, J.K.1    Getis, A.2
  • 57
    • 3042824653 scopus 로고    scopus 로고
    • Upper level set scan statistic for detecting arbitrarily shaped hotspots
    • Patil, G. P., and C. Taillie. 2004. Upper level set scan statistic for detecting arbitrarily shaped hotspots. Environmental and Ecological Statistics 11 (2): 183–97.
    • (2004) Environmental and Ecological Statistics , vol.11 , Issue.2 , pp. 183-197
    • Patil, G.P.1    Taillie, C.2
  • 58
    • 4344641521 scopus 로고    scopus 로고
    • Exploring spatial dependence of cotton yield using global and local autocorrelation statistics
    • Ping, J. L., C. J. Green, R. E. Zartman, and K. F. Bronson. 2004. Exploring spatial dependence of cotton yield using global and local autocorrelation statistics. Field Crops Research 89 (2): 219–36.
    • (2004) Field Crops Research , vol.89 , Issue.2 , pp. 219-236
    • Ping, J.L.1    Green, C.J.2    Zartman, R.E.3    Bronson, K.F.4
  • 59
    • 84950632109 scopus 로고
    • Objective criteria for the evaluation of clustering methods
    • Rand, W. M. 1971. Objective criteria for the evaluation of clustering methods. Journal of the American Statistical Association 66 (336): 846–50.
    • (1971) Journal of the American Statistical Association , vol.66 , Issue.336 , pp. 846-850
    • Rand, W.M.1
  • 60
    • 84950648422 scopus 로고
    • Cluster analysis and mathematical programming
    • Rao, M. R. 1971. Cluster analysis and mathematical programming. Journal of the American Statistical Association 66 (335): 622–26.
    • (1971) Journal of the American Statistical Association , vol.66 , Issue.335 , pp. 622-626
    • Rao, M.R.1
  • 61
    • 0034897670 scopus 로고    scopus 로고
    • A statistical method for the detection of geographic clustering
    • Rogerson, P. A. 2001. A statistical method for the detection of geographic clustering. Geographical Analysis 33 (3): 215–27.
    • (2001) Geographical Analysis , vol.33 , Issue.3 , pp. 215-227
    • Rogerson, P.A.1
  • 64
    • 2442439674 scopus 로고    scopus 로고
    • A comparison of document clustering techniques
    • Steinbach, M., G. Karypis, and V. Kumar. 2000. A comparison of document clustering techniques. KDD Workshop on Text Mining 400 (1): 525–26.
    • (2000) KDD Workshop on Text Mining , vol.400 , Issue.1 , pp. 525-526
    • Steinbach, M.1    Karypis, G.2    Kumar, V.3
  • 65
    • 0034731824 scopus 로고    scopus 로고
    • A test for spatial disease clustering adjusted for multiple testing
    • Tango, T. 2000. A test for spatial disease clustering adjusted for multiple testing. Statistics in Medicine 19 (2): 191–204.
    • (2000) Statistics in Medicine , vol.19 , Issue.2 , pp. 191-204
    • Tango, T.1
  • 66
    • 24144490300 scopus 로고    scopus 로고
    • A flexibly shaped spatial scan statistic for detecting clusters
    • Tango, T., and K. Takahashi. 2005. A flexibly shaped spatial scan statistic for detecting clusters. International Journal of Health Geographics 4 (1): 11.
    • (2005) International Journal of Health Geographics , vol.4 , Issue.1 , pp. 11
    • Tango, T.1    Takahashi, K.2
  • 70
    • 34147216291 scopus 로고    scopus 로고
    • A comparison of spatial clustering and cluster detection techniques for childhood leukemia incidence in Ohio, 1996–2003
    • Wheeler, D. 2007. A comparison of spatial clustering and cluster detection techniques for childhood leukemia incidence in Ohio, 1996–2003. International Journal of Health Geographics 6 (1): 13.
    • (2007) International Journal of Health Geographics , vol.6 , Issue.1 , pp. 13
    • Wheeler, D.1
  • 71
    • 84908182314 scopus 로고    scopus 로고
    • Williamson, B., and I. Guyon. 2012. Clustering: Science or art? Journal of Machine Learning Research 27:65–80.
  • 72
    • 0035091351 scopus 로고    scopus 로고
    • Providing spatial statistical data analysis functionality for the GIS user: The SAGE project
    • Wise, S., R. Haining, and J. Ma. 2001. Providing spatial statistical data analysis functionality for the GIS user: The SAGE project. International Journal of Geographical Information Science 15 (3): 239–54.
    • (2001) International Journal of Geographical Information Science , vol.15 , Issue.3 , pp. 239-254
    • Wise, S.1    Haining, R.2    Ma, J.3
  • 73
    • 78349307458 scopus 로고    scopus 로고
    • Identifying irregularly shaped crime hot-spots using a multiobjective evolutionary algorithm
    • Wu, X., and T. H. Grubesic. 2010. Identifying irregularly shaped crime hot-spots using a multiobjective evolutionary algorithm. Journal of Geographical Systems 12 (4): 409–33.
    • (2010) Journal of Geographical Systems , vol.12 , Issue.4 , pp. 409-433
    • Wu, X.1    Grubesic, T.H.2


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