Clustering Methodology for Symbolic Data

Description

Contents......Page 3 Introduction......Page 6 Symbolic Data Basics......Page 12 Individuals, Classes, Observations & Descriptions......Page 13 Types of Symbolic Data......Page 14 How do Symbolic Data arise......Page 22 Descriptive Statistics......Page 29 Other Issues......Page 43 Exercises......Page 44 General Basic Definitions......Page 52 Distance Measures - List or Multi-valued Data......Page 60 Distance Measures - Interval Data......Page 67 Exercises......Page 84 Dissimilarity/Distance Measures - Modal Multi-valued List Data......Page 88 Dissimilarity/Distance Measures - HistogramData......Page 98 Exercises......Page 123 Brief Overview of Clustering......Page 124 Partitioning......Page 125 Hierarchies......Page 130 Illustration......Page 136 Other Issues......Page 151 Partitioning Techniques......Page 153 Basic Partitioning Concepts......Page 154 Multi-valued List Observations......Page 157 Interval-valued Data......Page 163 Histogram Observations......Page 173 Mixed-valued Observations......Page 181 Mixture Distribution Methods......Page 183 Cluster Representation......Page 190 Other Issues......Page 193 Exercises......Page 195 Some Basics......Page 201 Monothetic Methods......Page 207 Polythethic Methods......Page 240 Stopping Rule......Page 254 Other Issues......Page 261 Exercises......Page 262 Agglomerative Hierarchical Clustering......Page 265 Pyramidal Clustering......Page 293 Exercises......Page 317 Appendix......Page 319 Refs......Page 321 Index......Page 334