-
1
-
-
0001941306
-
Cluster analysis in marketing research
-
R. P. Bagozzi Ed, Oxford: Blackwell
-
Arabie, P., & Hubert, L. (1994). Cluster analysis in marketing research. In R. P. Bagozzi (Ed.), Advanced methods of marketing research (pp. 160-189). Oxford: Blackwell.
-
(1994)
Advanced methods of marketing research
, pp. 160-189
-
-
Arabie, P.1
Hubert, L.2
-
2
-
-
0007419971
-
Data-based metrics for cluster analysis
-
Art, D., Gnanadesikan, R., & Kettenring, J. R. (1982). Data-based metrics for cluster analysis. Utilitas Mathematicas, 21A, 75-99.
-
(1982)
Utilitas Mathematicas
, vol.21 A
, pp. 75-99
-
-
Art, D.1
Gnanadesikan, R.2
Kettenring, J.R.3
-
3
-
-
10844257374
-
Clustering binary data in the presence of masking variables
-
Brusco, M. J. (2004). Clustering binary data in the presence of masking variables. Psychological Methods, 9, 510-523.
-
(2004)
Psychological Methods
, vol.9
, pp. 510-523
-
-
Brusco, M.J.1
-
4
-
-
0035534927
-
A variable-selection heuristic for K-means clustering
-
Brusco, M. J., & Cradit, J. D. (2001). A variable-selection heuristic for K-means clustering. Psychometrika, 66, 249-270.
-
(2001)
Psychometrika
, vol.66
, pp. 249-270
-
-
Brusco, M.J.1
Cradit, J.D.2
-
5
-
-
38949174601
-
A comparison of heuristic procedures for minimum within-cluster sums of squares partitioning
-
in press
-
Brusco, M. J., & Steinley, D. (in press). A comparison of heuristic procedures for minimum within-cluster sums of squares partitioning. Psychometrika.
-
Psychometrika
-
-
Brusco, M.J.1
Steinley, D.2
-
9
-
-
0036011451
-
An examination of indexes for determining the number of clusters in binary data sets
-
Dimitriadou, E., Dolnicar, S., & Weingessel, A. (2002). An examination of indexes for determining the number of clusters in binary data sets. Psychometrika, 67, 137-160.
-
(2002)
Psychometrika
, vol.67
, pp. 137-160
-
-
Dimitriadou, E.1
Dolnicar, S.2
Weingessel, A.3
-
10
-
-
21844523554
-
Univariate screening measures for cluster analysis
-
Donoghue, J. R. (1995). Univariate screening measures for cluster analysis. Multivariate Behavioral Research, 30, 385-427.
-
(1995)
Multivariate Behavioral Research
, vol.30
, pp. 385-427
-
-
Donoghue, J.R.1
-
12
-
-
0000764772
-
The use of multiple measurements in taxonomic problems
-
Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7, 179-188.
-
(1936)
Annals of Eugenics
, vol.7
, pp. 179-188
-
-
Fisher, R.A.1
-
13
-
-
21844501258
-
Weighting and selection of variables for cluster analysis
-
Gnanadesikan, R., Kettenring, J. R., & Tsao, S. L. (1995). Weighting and selection of variables for cluster analysis. Journal of Classification, 12, 113-136.
-
(1995)
Journal of Classification
, vol.12
, pp. 113-136
-
-
Gnanadesikan, R.1
Kettenring, J.R.2
Tsao, S.L.3
-
15
-
-
0001457509
-
Some methods of classification and analysis of multivariate observations
-
L. M. Le Cam & J. Neyman Eds, Berkeley: University of California Press
-
MacQueen, J. (1967). Some methods of classification and analysis of multivariate observations. In L. M. Le Cam & J. Neyman (Eds.), Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability (Vol. 1, pp. 281-297). Berkeley: University of California Press.
-
(1967)
Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability
, vol.1
, pp. 281-297
-
-
MacQueen, J.1
-
17
-
-
33847457966
-
An examination of the effect of six types of error perturbation on fifteen clustering algorithms
-
Milligan, G. W. (1980). An examination of the effect of six types of error perturbation on fifteen clustering algorithms. Psychometrika, 45, 325-342.
-
(1980)
Psychometrika
, vol.45
, pp. 325-342
-
-
Milligan, G.W.1
-
18
-
-
0000272920
-
An algorithm for generating artificial test clusters
-
Milligan, G. W. (1985). An algorithm for generating artificial test clusters. Psychometrika, 50, 123-127.
-
(1985)
Psychometrika
, vol.50
, pp. 123-127
-
-
Milligan, G.W.1
-
19
-
-
0002048998
-
A validation study of a variable-weighting algorithm for cluster analysis
-
Milligan, G. W. (1989). A validation study of a variable-weighting algorithm for cluster analysis. Journal of Classification, 6, 53-71.
-
(1989)
Journal of Classification
, vol.6
, pp. 53-71
-
-
Milligan, G.W.1
-
20
-
-
0002271592
-
Clustering validation, results and implications for applied analysis
-
P. Arabie, L. J. Hubert, & G. De Soete Eds, River Edge, NJ: World Scientific
-
Milligan, G. W. (1996). Clustering validation, results and implications for applied analysis. In P. Arabie, L. J. Hubert, & G. De Soete (Eds.), Clustering and classification (pp. 341-375). River Edge, NJ: World Scientific.
-
(1996)
Clustering and classification
, pp. 341-375
-
-
Milligan, G.W.1
-
21
-
-
34250115918
-
An examination of procedures for determining the number of clusters in a data set
-
Milligan, G. W., & Cooper, M. C. (1985). An examination of procedures for determining the number of clusters in a data set. Psychometrika, 50, 159-179.
-
(1985)
Psychometrika
, vol.50
, pp. 159-179
-
-
Milligan, G.W.1
Cooper, M.C.2
-
22
-
-
84948872101
-
A study of the comparability of external criteria for hierarchical cluster analysis
-
Milligan, G. W., & Cooper, M. C. (1986). A study of the comparability of external criteria for hierarchical cluster analysis. Multivariate Behavioral Research, 21, 441-458.
-
(1986)
Multivariate Behavioral Research
, vol.21
, pp. 441-458
-
-
Milligan, G.W.1
Cooper, M.C.2
-
24
-
-
84895337544
-
Adaptive hierarchical clustering schemes
-
Rohlf, F. J. (1970). Adaptive hierarchical clustering schemes. Systematic Zoology, 19, 58-82.
-
(1970)
Systematic Zoology
, vol.19
, pp. 58-82
-
-
Rohlf, F.J.1
-
26
-
-
0142136684
-
K-means clustering: What you don't know may hurt you
-
Steinley, D. (2003). K-means clustering: What you don't know may hurt you. Psychological Methods, 8, 294-304.
-
(2003)
Psychological Methods
, vol.8
, pp. 294-304
-
-
Steinley, D.1
-
27
-
-
33744726077
-
Standardizing variables in K-means clustering
-
D. Banks, L. House, F. R. McMorris, P. Arabie, & W. Gaul Eds, New York: Springer
-
Steinley, D. (2004a). Standardizing variables in K-means clustering. In D. Banks, L. House, F. R. McMorris, P. Arabie, & W. Gaul (Eds.), Classification, clustering, and data mining applications (pp. 53-60). New York: Springer.
-
(2004)
Classification, clustering, and data mining applications
, pp. 53-60
-
-
Steinley, D.1
-
28
-
-
4344611435
-
Properties of the Hubert-Arabie adjusted Rand index
-
Steinley, D. (2004b). Properties of the Hubert-Arabie adjusted Rand index. Psychological Methods, 9, 386-396.
-
(2004)
Psychological Methods
, vol.9
, pp. 386-396
-
-
Steinley, D.1
-
30
-
-
33745700805
-
Profiling local optima in K-means clustering: Developing a diagnostic technique
-
Steinley, D. (2006b). Profiling local optima in K-means clustering: Developing a diagnostic technique. Psychological Methods, 11, 178-192.
-
(2006)
Psychological Methods
, vol.11
, pp. 178-192
-
-
Steinley, D.1
-
31
-
-
34250871625
-
Initializing K-means clustering: A critical analysis of several techniques
-
Steinley, D., & Brusco, M. J. (2007). Initializing K-means clustering: A critical analysis of several techniques. Journal of Classification, 24, 99-121.
-
(2007)
Journal of Classification
, vol.24
, pp. 99-121
-
-
Steinley, D.1
Brusco, M.J.2
-
32
-
-
33744720321
-
OCLUS: An analytic method for generating clusters with known overlap
-
Steinley, D., & Henson, R. (2005). OCLUS: An analytic method for generating clusters with known overlap. Journal of Classification, 22, 221-250.
-
(2005)
Journal of Classification
, vol.22
, pp. 221-250
-
-
Steinley, D.1
Henson, R.2
-
33
-
-
0018604771
-
Standardization of measures prior to cluster analysis
-
Stoddard, A. M. (1979). Standardization of measures prior to cluster analysis. Biometrics, 35, 765-773.
-
(1979)
Biometrics
, vol.35
, pp. 765-773
-
-
Stoddard, A.M.1
-
34
-
-
0035532141
-
Estimating the number of clusters in a data set via the gap statistic
-
Tibshirani, R., Walther, G., & Hastie, T. (2001). Estimating the number of clusters in a data set via the gap statistic. Journal of the Royal Statistical Society B, 63, 411-423.
-
(2001)
Journal of the Royal Statistical Society B
, vol.63
, pp. 411-423
-
-
Tibshirani, R.1
Walther, G.2
Hastie, T.3
-
35
-
-
84942904298
-
Importance of individual variables in the K-means algorithm
-
D. Cheung, G. J. Williams, & Q. Li Eds, Berlin: Springer
-
Vesanto, J. (2001). Importance of individual variables in the K-means algorithm. In D. Cheung, G. J. Williams, & Q. Li (Eds.), Proceedings of the Pacific-Asia Conference in Knowledge Discovery and Data Mining (pp. 513-518). Berlin: Springer.
-
(2001)
Proceedings of the Pacific-Asia Conference in Knowledge Discovery and Data Mining
, pp. 513-518
-
-
Vesanto, J.1
-
36
-
-
0033408148
-
A method for generating simulated plasmodes and artificial test clusters with user-defined shape, size, and orientation
-
Waller, N. G., Underhill, J. M., & Kaiser, H. A. (1999). A method for generating simulated plasmodes and artificial test clusters with user-defined shape, size, and orientation. Multivariate Behavioral Research, 34, 123-142.
-
(1999)
Multivariate Behavioral Research
, vol.34
, pp. 123-142
-
-
Waller, N.G.1
Underhill, J.M.2
Kaiser, H.A.3
-
37
-
-
84944178665
-
Hierarchical grouping to optimize an objective function
-
Ward, J. H. (1963). Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association, 58, 236-244.
-
(1963)
Journal of the American Statistical Association
, vol.58
, pp. 236-244
-
-
Ward, J.H.1
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