Abstract
To replicate a cluster analysis, clusters must first be described in terms of an objective classification rule. The effectiveness of three rules (nearest neighbor classification, nearest centroid assignment, and quadratic discriminant analysis) for replicating Ward's algorithm (Ward, 1963) is evaluated by Monte Carlo study. Consistent replication links clusters and their replicas identically over alternative cross-validation sequences (i.e., A replicates B, B replicates A) and is associated with recovery of known clusters. Replication using nearest neighbor classification results in superior goodness-of-fit, more frequent consistent replication, and significant prediction of recovery. Although moderate or greater replication dentoes good recovery, replication is not a necessary condition of recovery of true clusters.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
