TY  - JOUR
AU  - Dhillon, Inderjit S.
AU  - Modha, Dharmendra S.
AU  - Spangler, W. Scott
T1  - Class visualization of high-dimensional data with applications
JO  - Computational Statistics & Data Analysis
PY  - 2002/november
VL  - 41
IS  - 1
SP  - 59
EP  - 90
UR  - http://www.cs.utexas.edu/~inderjit/public_papers/csda.pdf
DO  - 
KW  - alphaworks
KW  - cluster
KW  - clustering
KW  - dm
KW  - visualization
L1  - 
SN  - 
N1  - 
N1  - 
AB  - No abstract is available for this item.
ER  -

TY  - JOUR
AU  - Bezdek, J. C.
AU  - Li, W. Q.
AU  - Attikiouzel, Y.
AU  - Windham, M.
T1  - A geometric approach to cluster validity for normal mixtures
JO  - Soft Computing - A Fusion of Foundations, Methodologies and Applications
PY  - 1997/12
VL  - 1
IS  - 4
SP  - 166
EP  - 179
UR  - http://dx.doi.org/10.1007/s005000050019
DO  - 
KW  - cluster
KW  - evaluation
KW  - index
L1  - 
SN  - 
N1  - SpringerLink - Journal Article
N1  - 
AB  - We study indices for choosing the correct number of components in a mixture of normal distributions. Previous studies have been confined to indices based wholly on probabilistic models. Viewing mixture decomposition as probabilistic clustering (where the emphasis is on partitioning for geometric substructure) as opposed to parametric estimation enables us to introduce both fuzzy and crisp measures of cluster validity for this problem. We presume the underlying samples to be unlabeled, and use the expectation-maximization (EM) algorithm to find clusters in the data. We test 16 probabilistic, 3 fuzzy and 4 crisp indices on 12 data sets that are samples from bivariate normal mixtures having either 3 or 6 components. Over three run averages based on different initializations of EM, 10 of the 23 indices tested for choosing the right number of mixture components were correct in at least 9 of the 12 trials. Among these were the fuzzy index of Xie-Beni, the crisp Davies-Bouldin index, and two crisp indices that are recent generalizations of Dunn's index.
<p>ER  -
ER  -

TY  - BOOK
AU  - Kaufman, L.
AU  - Rousseeuw, P. J.
A2  - 
T1  - Finding Groups in Data: An Introduction to Cluster Analysis
PB  - John Wiley
C1  - 
PY  - 1990/
VL  - 
IS  - 
SP  - 
EP  - 
UR  - 
DO  - 
KW  - clustering
KW  - evaluation
KW  - cluster
L1  - 
SN  - 1-58133-109-7
N1  - 
N1  - 
AB  - 
ER  -

TY  - JOUR
AU  - Rand, W.M.
T1  - Objective criteria for the evaluation of clustering methods
JO  - Journal of the American Statistical Association 
PY  - 1971/
VL  - 66
IS  - 336
SP  - 846
EP  - 850
UR  - 
DO  - 
KW  - cluster
KW  - clustering
KW  - criteria
KW  - evaluation
KW  - index
KW  - rand
L1  - 
SN  - 
N1  - 
N1  - 
AB  - 
ER  -