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

ISBN-13: 9783540436911 / Angielski / Miękka / 2002 / 508 str.

International Federation of Classification Societies; Krzystof Jajuga; Andrzej Sokolowski

Opis

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.

Spis treści

I. Clustering and Discrimination.- Clustering.- Some Thoughts about Classification.- Partial Defuzzification of Fuzzy Clusters.- A New Clustering Approach, Based on the Estimation of the Probability Density Function, for Gene Expression Data.- Two-mode Partitioning: Review of Methods and Application of Tabu Search.- Dynamical Clustering of Interval Data Optimization of an Adequacy Criterion Based on Hausdorff Distance.- Removing Separation Conditions in a 1 against 3-Components Gaussian Mixture Problem.- Obtaining Partitions of a Set of Hard or Fuzzy Partitions.- Clustering for Prototype Selection using Singular Value Decomposition.- Clustering in High-dimensional Data Spaces.- Quantization of Models: Local Approach and Asymptotically Optimal Partitions.- The Performance of an Autonomous Clustering Technique.- Cluster Analysis with Restricted Random Walks.- Missing Data in Hierarchical Classification of Variables — a Simulation Study.- Cluster Validation.- Representation and Evaluation of Partitions.- Assessing the Number of Clusters of the Latent Class Model..- Validation of Very Large Data Sets Clustering by Means of a Nonparametric Linear Criterion.- Discrimination.- Effect of Feature Selection on Bagging Classifiers Based on Kernel Density Estimators.- Biplot Methodology for Discriminant Analysis Based upon Robust Methods and Principal Curves.- Bagging Combined Classifiers.- Application of Bayesian Decision Theory to Constrained Classification Networks.- II. Multivariate Data Analysis and Statistics.- Multivariate Data Analysis.- Quotient Dissimilarities, Euclidean Embeddability, and Huygens’ Weak Principle.- Conjoint Analysis and Stimulus Presentation — a Comparison of Alternative Methods.- Grade Correspondence-cluster Analysis Applied to Separate Components of Reversely Regular Mixtures.- Obtaining Reducts with a Genetic Algorithm.- A Projection Algorithm for Regression with Collinearity.- Confronting Data Analysis with Constructivist Philosophy.- Statistical Methods.- Maximum Likelihood Clustering with Outliers.- An Improved Method for Estimating the Modes of the Probability Density Function and the Number of Classes for PDF-based Clustering.- Maximization of Measure of Allowable Sample Sizes Region in Stratified Sampling.- On Estimation of Population Averages on the Basis of Cluster Sample.- Symbolic Data Analysis.- Symbolic Regression Analysis.- Modelling Memory Requirement with Normal Symbolic Form.- Mixture Decomposition of Distributions by Copulas.- Determination of the Number of Clusters for Symbolic Objects Described by Interval Variables.- Symbolic Data Analysis Approach to Clustering Large Datasets.- Symbolic Class Descriptions.- Consensus Trees and Phylogenetics.- A Comparison of Alternative Methods for Detecting Reticulation Events in Phylogenetic Analysis.- Hierarchical Clustering of Multiple Decision Trees.- Multiple Consensus Trees.- A Family of Average Consensus Methods for Weighted Trees.- Comparison of Four methods for Inferring Additive Trees from Incomplete Dissimilarity Matrices.- Quartet Trees as a Tool to Reconstruct Large Trees from Sequences.- Regression Trees.- Regression Trees for Longitudinal Data with Time-dependent Covariates.- Tree-based Models in Statistics: Three Decades of Research.- Computationally Efficient Linear Regression Trees.- Neural Networks and Genetic Algorithms.- A Clustering Based Procedure for Learning the Hidden Unit Parameters in Elliptical Basis Function Networks.- Multi-layer Perceptron on Interval Data.- III. Applications.- Textual Analysis of Customer Statements for Quality Control and Help Desk Support.- AHP as Support for Strategy Decision Making in Banking.- Bioinformatics and Classification: The Analysis of Genome Expression Data.- Glaucoma Diagnosis by Indirect Classifiers.- A Cluster Analysis of the Importance of Country and Sector on Company Returns.- Problems of Classification in Investigative Psychology.- List of Reviewers.