Classification, Clustering, and Data Mining Applications: Proceedings of the Meeting of the International Federation of Classification Societies (IFCS [Paperback]

Modern data analysis stands at the interface of statistics, computer science, and discrete mathematics. This volume describes new methods in this area, with special emphasis on classification and cluster analysis. Those methods are applied to problems in information retrieval, phylogeny, medical diagnosis, microarrays, and other active research areas.I New Methods in Cluster Analysis.- Thinking Ultrametrically.- Clustering by Vertex Density in a Graph.- Clustering by Ant Colony Optimization.- A Dynamic Cluster Algorithm Based on Lr Distances for Quantitative Data.- The Last Step of a New Divisive Monothetic Clustering Method: the Gluing-Back Criterion.- Standardizing Variables in K-means Clustering.- A Self-Organizing Map for Dissimilarity Data.- Another Version of the Block EM Algorithm.- Controlling the Level of Separation of Components in Monte Carlo Studies of Latent Class Models.- Fixing Parameters in the Constrained Hierarchical Classification Method: Application to Digital Image Segmentation.- New Approaches for Sum-of-Diameters Clustering.- Spatial Pyramidal Clustering Based on a Tessellation.- II Modern Nonparametrics.- Relative Projection Pursuit and its Application.- Priors for Neural Networks.- Combining Models in Discrete Discriminant Analysis Through a Committee of Methods.- Phoneme Discrimination with Functional Multi-Layer Perceptrons.- PLS Approach for Clusterwise Linear Regression on Functional Data.- On Classification and Regression Trees for Multiple Responses.- Subsetting Kernel Regression Models Using Genetic Algorithm and the Information Measure of Complexity.- Cherry-Picking as a Robustness Tool.- III Classification and Dimension Reduction.- Academic Obsessions and Classification Realities: Ignoring Practicalities in Supervised Classification.- Modified Biplots for Enhancing Two-Class Discriminant Analysis.- Weighted Likelihood Estimation of Person Locations in an Unfolding Model for Polytomous Responses.- Classification of Geospatial Latticel³ì