## Classification, Clustering, and Data Analysis: Recent Advances and ApplicationsKrzystof Jajuga, Andrzej Sokolowski, Hans-Hermann Bock 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 |

### Other editions - View all

Classification, Clustering, and Data Analysis Krzystof Jajuga,Andrzej Sokolowski,Hans Hermann Bock No preview available - 2002 |

### Common terms and phrases

applied approach average Bayesian biplot Bock bootstrap Breiman categorical classification cluster analysis clustering algorithm clustering methods coefficient components compute conjoint consensus tree copulas corresponding covariance matrix Data Analysis data set data table decision trees decomposition defined denote density Diday dimensionality dissimilarity distance distribution estimation Euclidean example fuzzy gene expression genetic algorithm given glaucoma Hampel Hematocrit hierarchical clustering hybrid input interval iteration k-means kernel latent class model likelihood linear Machine Learning mean measure misclassification error mixture modes multivariate node normal number of clusters objects observations obtained optimal outliers paper parameters partition phylogenetic predictors principal curve probability problem procedure proposed prototypes quartet random regression trees robust sample selection sequence simulation Singular Value Decomposition solution split Springer statistical step structure subset symbolic data techniques text mining tion ultrametric values variables variance vector weighted