Classification and Clustering
eBook - PDF

Classification and Clustering

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

  1. 478 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Classification and Clustering

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

About this book

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.

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Yes, you can access Classification and Clustering by J. Van Ryzin in PDF and/or ePUB format, as well as other popular books in Matematica & Probabilità e statistica. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Academic Press
Year
2014
Print ISBN
9780127142500
eBook ISBN
9781483276618
Topic
Matematica
Subtopic
Probabilità e statistica

Table of contents

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