Classification and Clustering

Proceedings of an Advanced Seminar Conducted by the Mathematics Research Center, the University of Wisconsin at Madison, May 3–5, 1976

J. Van Ryzin

• Publisher: Academic Press
• Year: 2014
• Print ISBN:
  9780127142500
• eBook ISBN:
  9781483276618
• Topic: Mathematics
• Subtopic: Probability & Statistics
• Index: Mathematics

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.

Table of contents

• Front Cover
• Classification and Clustering
• Copyright Page
• Table of Contents
• List of Contributors
• Preface
• Chapter 1. Clustering and Classification: Background and Current Directions
• Chapter 2. The Relationship between Multidimensional Scaling and Clustering
• Chapter 3. Distribution Problems in Clustering
• Chapter 4. The Botryology of Botryology
• Chapter 5. Graph Theoretic Techniques for Cluster Analysis Algorithms
• Chapter 6. An Empirical Comparison of Baseline Models for Goodness-of-Fit in r-Diameter Hierarchical Clustering
• Chapter 7. Data Dependent Clustering Techniques
• Chapter 8. Cluster Analysis Applied to a Study of Race Mixture in Human Populations
• Chapter 9. Linguistic Approach to Pattern Recognition
• Chapter 10. Fuzzy Sets and Their Application to Pattern Classification and Clustering Analysis
• Chapter 11. Discrimination, Allocatory and Separatory, Linear Aspects
• Chapter 12. Discriminant Analysis When Scale Contamination Is Present in the Initial Sample
• Chapter 13. The Statistical Basis of Computerized Diagnosis Using the Electrocardiogram
• Chapter 14. Linear Discrimination and Some Further Results on Best Lower Dimensional Representations
• Chapter 15. A Simple Histogram Method for Nonparametric Classification
• Chapter 16. Optimal Smoothing of Density Estimates
• Index