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Classification and Clustering
Proceedings of an Advanced Seminar Conducted by the Mathematics Research Center, the University of Wisconsin at Madison, May 3–5, 1976
1st Edition - January 28, 1977
Editor: J. Van Ryzin
Language: English
eBook ISBN:9781483276618
9 7 8 - 1 - 4 8 3 2 - 7 6 6 1 - 8
Classification and Clustering documents the proceedings of the Advanced Seminar on Classification and Clustering held in Madison, Wisconsin on May 3-5, 1976. This compilation…Read more
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Classification and Clustering documents the proceedings of the Advanced Seminar on Classification and Clustering held in Madison, Wisconsin on May 3-5, 1976. This compilation discusses the relationship between multidimensional scaling and clustering, distribution problems in clustering, and botryology of botryology. The graph theoretic techniques for cluster analysis algorithms, data dependent clustering techniques, and linguistic approach to pattern recognition are also elaborated. This text likewise covers the discriminant analysis when scale contamination is present in the initial sample and statistical basis of computerized diagnosis using the electrocardiogram. Other topics include the simple histogram method for nonparametric classification and optimal smoothing of density estimates. This book is intended for mathematicians, biological scientists, social scientists, computer scientists, statisticians, and engineers interested in classification and clustering.
List of Contributors
Preface
Clustering and Classification: Background and Current Directions
The Relationship Between Multidimensional Scaling and Clustering
Distribution Problems in Clustering
The Botryology of Botryology
Graph Theoretic Techniques for Cluster Analysis Algorithms
An Empirical Comparison of Baseline Models for Goodness-of-Fit in r-Diameter Hierarchical Clustering
Data Dependent Clustering Techniques
Cluster Analysis Applied to a Study of Race Mixture in Human Populations
Linguistic Approach to Pattern Recognition
Fuzzy Sets and Their Application to Pattern Classification and Clustering Analysis
Discrimination, Allocatory and Separatory, Linear Aspects
Discriminant Analysis When Scale Contamination Is Present in the Initial Sample
The Statistical Basis of Computerized Diagnosis Using the Electrocardiogram
Linear Discrimination and Some Further Results on Best Lower Dimensional Representations
A Simple Histogram Method for Nonparametric Classification