Access the full text.
Sign up today, get DeepDyve free for 14 days.
Loading next page...
/lp/springer-journals/a-note-on-maximizing-the-agreement-between-partitions-a-stepwise-AjmjrWxoB0
References (20)
-
D. Steinley (2004)
Properties of the Hubert-Arabie adjusted Rand index.Psychological methods, 9 3
-
A. Hardy (1994)
An examination of procedures for determining the number of clusters in a data set -
H. Messatfa (1992)
An algorithm to maximize the agreement between partitionsJournal of Classification, 9
-
(1987)
Methodological Review: Clustering Methods -
A. Albatineh, M. Niewiadomska-Bugaj, D. Mihalko (2006)
On Similarity Indices and Correction for Chance AgreementJournal of Classification, 23
-
G. Milligan, M. Cooper (1986)
A Study of the Comparability of External Criteria for Hierarchical Cluster Analysis.Multivariate behavioral research, 21 4
-
(1980)
Comparing Classifications: An Evaluation of Several Coefficients of Partition Agreement”, paper presented at the meeting of the Classification -
D. Steinley (2003)
Local optima in K-means clustering: what you don't know may hurt you.Psychological methods, 8 3
-
E. Fowlkes, C. Mallows (1983)
A Method for Comparing Two Hierarchical ClusteringsJournal of the American Statistical Association, 78
-
J. Breckenridge (1989)
Replicating Cluster Analysis: Method, Consistency, and Validity.Multivariate behavioral research, 24 2
-
M. Brusco, J. Cradit (2001)
A variable-selection heuristic for K-means clusteringPsychometrika, 66
-
M. Brusco, D. Steinley (2008)
A Binary Integer Program to Maximize the Agreement Between PartitionsJournal of Classification, 25
-
D. Steinley, M. Brusco (2007)
Initializing K-means Batch Clustering: A Critical Evaluation of Several TechniquesJournal of Classification, 24
-
G. Milligan, M. Cooper (1988)
A study of standardization of variables in cluster analysisJournal of Classification, 5
-
M. Brusco (2004)
Clustering binary data in the presence of masking variables.Psychological methods, 9 4
-
G. Milligan, R. Cheng (1996)
Measuring the influence of individual data points in a cluster analysisJournal of Classification, 13
-
D. Steinley (2004)
Standardizing Variables in K -means Clustering -
D. Steinley (2006)
Profiling local optima in K-means clustering: developing a diagnostic technique.Psychological methods, 11 2
-
G. Milligan (1996)
CLUSTERING VALIDATION: RESULTS AND IMPLICATIONS FOR APPLIED ANALYSES -
L. Collins, C. Dent (1988)
Omega: A General Formulation of the Rand Index of Cluster Recovery Suitable for Non-disjoint Solutions.Multivariate behavioral research, 23 2
- Publisher
- Springer Journals
- Copyright
- Copyright © 2015 by Classification Society of North America
- Subject
- Statistics; Statistical Theory and Methods; Pattern Recognition; Bioinformatics; Signal, Image and Speech Processing; Psychometrics; Marketing
- ISSN
- 0176-4268
- eISSN
- 1432-1343
- DOI
- 10.1007/s00357-015-9169-z
- Publisher site
- See Article on Publisher Site
Abstract
Building on Brusco and Steinley (2008), a computationally efficient stepwise optimal heuristic is provided for maximizing the adjusted Rand index (Hubert and Arabie 1985). The proposed algorithm is different than other methods for estimating the maximum value for the adjusted Rand index (e.g., Messatfa 1992) in that it does not rely on mathematical programming; consequently, problems of much larger size can be handled. Using the proposed method, various characteristics of the adjusted Rand index are explored and presented.
Journal
Journal of Classification – Springer Journals
Published: Mar 11, 2015