Advanced SearchSearch Tips
Cluster Analysis Using Principal Coordinates for Binary Data
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Cluster Analysis Using Principal Coordinates for Binary Data
Chae, Seong-San; Kim, Jeong, Il;
  PDF(new window)
The results of using principal coordinates prior to cluster analysis are investigated on the samples from multiple binary outcomes. The retrieval ability of the known clustering algorithm is significantly improved by using principal coordinates instead of using the distance directly transformed from four association coefficients for multiple binary variables.
Agglomerative Clustering Algorithm;Principal Coordinates;Association Coefficients;
 Cited by
Cluster Analysis with Balancing Weight on Mixed-type Data,;;;

Communications for Statistical Applications and Methods, 2006. vol.13. 3, pp.719-732 crossref(new window)
Affi, A.A. and Clark, V.(1990). Computer-Aided Multivariate Analysis, Van Nostrand Reinhold Company, New York

Asparoukhov, O.K. and Krzanowski, W.J.(2001). A comparison of discriminant procedures for binary variables, Computational Statistics & Data Analysis, Vol. 38, 139-160 crossref(new window)

Chae, S.S. and Warde, W.D.(1991). A method to predict the number of clusters, Journal of the Korean Statistical Society, Vol. 20, 162-176

Chae, S.S. and Warde, W.D.(2006). Effect of using principal coordinates and principal components on retrieval of clusters, Computational Statistics & Data Analysis, Vol. 50, 1407-1417 crossref(new window)

DuBien, J.L. and Warde, W.D.(1979). A mathematical comparison of the members of an infinite family of agglomerative clustering algorithms, The Canadian Journal of Statistics, Vol. 7, 29-38 crossref(new window)

DuBien, J.L. and Warde, W.D.(1987), A comparison of agglomerative clustering methods with respect to noise, Communications in Statistics, Theory and Method, Vol. 16, 1433-1460 crossref(new window)

DuBien, J.L., Warde, W.D. and Chae, S.S.(2004). Moments of Rand's C statistic in cluster analysis, Statistics & Probability Letters, Vol. 69, 243-252 crossref(new window)

Gower, J.C.(1966). Some distance properties of latent root and vector methods used in multivariate analysis, Biometrika, Vol. 53, 325-338 crossref(new window)

Gower, J.C.(1971). A general coefficient of similarity and some of its properties, Biometrics, Vol. 27, 857-871 crossref(new window)

Gower, J.C. and Legendre, P.(1986). Metric and Euclidean properties of dissimilarity coefficients, Journal of Classification, Vol. 3, 5-48 crossref(new window)

Huang, Z.(1998). Extensions to the k-means algorithms for clustering large data sets with categorical values, Data mining and Knowledge Discovery, Vol. 2, 283-304 crossref(new window)

Lee, J.J.(2005). Discriminant analysis of binary data with multinomial distribution by using the iterative cross entropy minimization estimation, The Korean Communications in Statistics, Vol. 12, 125-137 crossref(new window)

Ordonez, C.(2003). Clustering binary data streams with K-means, In 8th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery

Rand, W.M.(1971). Objective criteria for the evaluation of clustering methods, Journal of the American Statistical Association, Vol. 66, 846-850 crossref(new window)