Hierarchical Clustering Algorithms with Influence Detection
| Autor: | Glenn W. Milligan, Richard Cheng |
|---|---|
| Rok vydání: | 1995 |
| Předmět: |
Fuzzy clustering
Computer science Applied Mathematics 05 social sciences Correlation clustering Single-linkage clustering 050401 social sciences methods 050301 education computer.software_genre Education Hierarchical clustering 0504 sociology CURE data clustering algorithm Consensus clustering Developmental and Educational Psychology Data mining Hierarchical clustering of networks Cluster analysis 0503 education computer Applied Psychology |
| Zdroj: | Educational and Psychological Measurement. 55:237-244 |
| ISSN: | 1552-3888 0013-1644 |
| DOI: | 10.1177/0013164495055002007 |
| Popis: | The computer program described in this study is based on the methodology developed by the authors to identify those individual data points that can affect the results of a cluster analysis. The computer program designed to compute the measure of internal influence is integrated with nine hierarchical clustering methods. Included among the methods is the first release of the Belbin, Faith, and Milligan 5-flexible clustering algorithm. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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