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Tree Models of Similarity and Association
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Tree Models of Similarity and Association



April 1996 | 72 pages | SAGE Publications, Inc
Clustering and tree models are widely used in the social and biological sciences to analyze similarity relations. Tree Models of Similarity and Association describes how matrices of similarities or associations among entities can be modeled using trees, and to explain some of the issues that arise in performing such analyses and correctly interpreting the results. James E. Corter clearly distinguishes ultrametric trees (fit by the techniques widely known as "hierarchical clustering") from additive trees and discusses how specific aspects of each type of tree can be interpreted through the use of applications as examples. He concludes with a discussion of when tree models might be preferable to spatial geometric models, such as those fit by multidimensional scaling (MDS) or principal components analysis (PCA).

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Introduction
 
Two Types of Tree Models
 
Algorithms for Fitting Trees to Data
 
Practical Issues and Applications
 
Some Extensions of Tree Models
 
Discussions and Conclusions
 
Appendix A: Mathematical Programming
 
Appendix B: Availability of Software for Fitting Trees
 
Appendix C: Estimating Fit of a Tree Using Multiple Regression

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ISBN: 9780803957077
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