A new ensemble method for cluster analysis is introduced, which can be interpreted in two different ways: As complexity-reducing preprocessing stage for hierarchical clustering and as combination procedure for several partitioning results. The basic idea is to locate and combine structurally stable cluster centers and/or prototypes. Random effects of the training set are reduced by repeatedly training on resampled sets (bootstrap samples). We discuss the algorithm both from a more theoretical and an applied point of view and demonstrate it on several data sets. (author's abstract) / Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"
| Identifer | oai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:epub-wu-01_1b0 |
| Date | January 1999 |
| Creators | Leisch, Friedrich |
| Publisher | SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business |
| Source Sets | Wirtschaftsuniversität Wien |
| Language | English |
| Detected Language | English |
| Type | Paper, NonPeerReviewed |
| Format | application/pdf |
| Relation | http://epub.wu.ac.at/1272/ |
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