Classification, Clustering, and Data Analysis: Recent Advances and Applications

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Krzystof Jajuga, Andrzej Sokolowski, Hans-Hermann Bock
Springer Science & Business Media, Dec 6, 2012 - Computers - 508 pages
The present volume contains a selection of papers presented at the Eighth Conference of the International Federation of Classification Societies (IFCS) which was held in Cracow, Poland, July 16-19, 2002. All originally submitted papers were subject to a reviewing process by two independent referees, a procedure which resulted in the selection of the 53 articles presented in this volume. These articles relate to theoretical investigations as well as to practical applications and cover a wide range of topics in the broad domain of classifi cation, data analysis and related methods. If we try to classify the wealth of problems, methods and approaches into some representative (partially over lapping) groups, we find in particular the following areas: • Clustering • Cluster validation • Discrimination • Multivariate data analysis • Statistical methods • Symbolic data analysis • Consensus trees and phylogeny • Regression trees • Neural networks and genetic algorithms • Applications in economics, medicine, biology, and psychology. Given the international orientation of IFCS conferences and the leading role of IFCS in the scientific world of classification, clustering and data anal ysis, this volume collects a representative selection of current research and modern applications in this field and serves as an up-to-date information source for statisticians, data analysts, data mining specialists and computer scientists.
 

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Contents

Partial Defuzzification of Fuzzy Clusters
27
Review of Methods and Application
43
Removing Separation Conditions in a 1 against 3Components
61
Obtaining Partitions of a Set of Hard or Fuzzy Partitions 75
74
Clustering in Highdimensional Data Spaces
89
The Performance of an Autonomous Clustering Technique 107
106
Cluster Analysis with Restricted Random Walks
113
Missing Data in Hierarchical Classification of Variables
121
Determination of the Number of Clusters for Symbolic
311
Symbolic Data Analysis Approach to Clustering Large
319
Symbolic Class Descriptions
329
A Comparison of Alternative Methods for Detecting Reticu
341
Hierarchical Clustering of Multiple Decision Trees 349
348
Multiple Consensus Trees
359
A Family of Average Consensus Methods for Weighted Trees
365
Quartet Trees as a Tool to Reconstruct Large Trees from
379

Representation and Evaluation of Partitions
131
Assessing the Number of Clusters of the Latent Class Model
139
Validation of Very Large Data Sets Clustering by Means of
147
Effect of Feature Selection on Bagging Classifiers Based
161
Biplot Methodology for Discriminant Analysis Based upon
169
Bagging Combined Classifiers
177
Application of Bayesian Decision Theory to Constrained Clas
185
Quotient Dissimilarities Euclidean Embeddability and Huy
195
Conjoint Analysis and Stimulus Presentation
203
Obtaining Reducts with a Genetic Algorithm
219
Confronting Data Analysis with Constructivist Philosophy
235
An Improved Method for Estimating the Modes of the Prob
257
On Estimation of Population Averages on the Basis of Cluster
270
Modelling Memory Requirement with Normal Symbolic Form
289
Regression Trees for Longitudinal Data with Timedependent
391
Three Decades of Research
399
Computationally Efficient Linear Regression Trees 409
408
Neural Networks and Genetic Algorithms
417
Multilayer Perceptron on Interval Data
427
Textual Analysis of Customer Statements for Quality Control
437
AHP as Support for Strategy Decision Making in Banking 447
446
The Analysis of Genome
455
Glaucoma Diagnosis by Indirect Classifiers 463
462
A Cluster Analysis of the Importance of Country and Sector
471
Problems of Classification in Investigative Psychology
479
List of Reviewers
488
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