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Cover image for Classification, clustering, and data Mining applications :  Proceedings of the Meeting of the International Federation of Classification Societies
Title:
Classification, clustering, and data Mining applications : Proceedings of the Meeting of the International Federation of Classification Societies
Series:
Studies in classification, data analysis, and knowledge organization
Publication Information:
Berlin : Springer, 2004
ISBN:
9783540220145
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Item Category 1
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30000010122214 QA278 I574 2004 Open Access Book Book
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Summary

Summary

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.


Table of Contents

Fionn MurtaghAlain GuénocheJavier Trejos and Alex Murillo and Eduardo PizaFrancisco de A. T. de Carvalho and Yves Lechevallier and Renata M.C.R. deSouzaJean- Yves Pirçon and Jean-Paul RassonDouglas SteinleyAïcha El Golii and Brieuc Conan-Guez and Fabrice RossiMohamed Nadif and Gérard GovaertJosé G. DiasKaddour Bachar and Israël-César LermanSarnath Ramnath and Mynul H. Khan, and Zubair ShamsEdwin DidayMasahiro Mizuta and Shintaro HiroHerbert K.H.LeeAna Sousa FerreiraBrieuc Conan-Guez and Fabrice RossiCristian Preda and Gilbert SaportaSeong Keon LeeXinli Bao and Hamparsum BozdoganLeanna L. House and David BanksDavid J. HandSugnet Gardner and Niel le RouxGuanzhong Luo and David AndrichKoji KuriharaXiaodong Lin and Yu ZhuJoseph LucasRaphaël Couturier and Régis Gras and Fabrice GuilletStefan Born and Lars Schmidt-ThiemeRosanna VerdeL. BillardAndré Hardy and Pascale LallemandMarie ChaventChérif Mballo and Edwin DidayRenata M.C.R. de Souza and Francisco de A.T. de Carvalho and Camilo P.Tenório and Yves LechevallierSérgio R. de M. Queiroz and Francisco de A. T. de CarvalhoMohamed Mehdi Limam and Edwin Diday and Suzanne WinsbergGeorges Hébrail and Yves LechevallierTobias Dezulian and Mike SteelFlorent Domenach and Bruno LeclercF. Afonso and L. Billard and E. DidayVladimir Makarenkov and Alix Boc and Abdoulaye Baniré DialloSusan J. Simmons and Xiaodong Lin and Chris Beecher and Young Truong and S. Stanley YoungGilles Clermont and Carson C. Chow and Gregory M. Constantine and YoramVodovotz and John BartelsMark G. VangelNicholas I. Bohnen and Marius G. Buliga and Gregory M. ConstantineVahan Grigoryan and Donald Chiarulli and Milos HauskrechtDaniel R. Jeske and Regina Y. LiuSimona Balbi and Emilio Di MeglioMarkus Demleitner and Michael Kurtz and Alberto Accomazzi and GüntherEichhorn and Carolyn S. Grant and Steven S. MurrayMaojin Jiang and Eric Jensen and Steve Beitzel and Shlomo ArgamonTao Tao and ChengXiang ZhaiMónica Bécue and Jérôme Pagès and Campo-Elías PardoAhu Sieg and Bamshad Mobasher and Robin BurkeWensheng Wu and Clement Yu and Weiyi MengStefano De Cantis and Antonino M. OliveriFrançois BavaudMichel TenenhausVincent LoonisAna Lorga da Silva and Gilbert Saporta and Helena Bacelar-NicolauEdgar Acuña and Caroline RodriguezKiri Wagstaff
Part I New Methods in Cluster Analysis
Thinking Ultrametricallyp. 3
Clustering by Vertex Density in a Graphp. 15
Clustering by Ant Colony Optimizationp. 25
A Dynamic Cluster Algorithm Based on L r Distances for Quantitative Datap. 33
The Last Step of a New Divisive Monothetic Clustering Method: the Gluing-Back Criterionp. 43
Standardizing Variables in K-means Clusteringp. 53
A Self-Organizing Map for Dissimilarity Datap. 61
Another Version of the Block EM Algorithmp. 69
Controlling the Level of Separation of Components in Monte Carlo Studies of Latent Class Modelsp. 77
Fixing Parameters in the Constrained Hierarchical Classification Method: Application to Digital Image Segmentationp. 85
New Approaches for Sum-of-Diameters Clusteringp. 95
Spatial Pyramidal Clustering Based on a Tessellationp. 105
Part II Modern Nonparametrics
Relative Projection Pursuit and its Applicationp. 123
Priors for Neural Networksp. 141
Combining Models in Discrete Discriminant Analysis Through a Committee of Methodsp. 151
Phoneme Discrimination with Functional Multi-Layer Perceptronsp. 157
PLS Approach for Clusterwise Linear Regression on Functional Datap. 167
On Classification and Regression Trees for Multiple Responsesp. 177
Subsetting Kernel Regression Models Using Genetic Algorithm and the Information Measure of Complexityp. 185
Cherry-Picking as a Robustness Toolp. 197
Part III Classification and Dimension Reduction
Academic Obsessions and Classification Realities: Ignoring Practicalities in Supervised Classificationp. 209
Modified Biplots for Enhancing Two-Class Discriminant Analysisp. 233
Weighted Likelihood Estimation of Person Locations in an Unfolding Model for Polytomous Responsesp. 241
Classification of Geospatial Lattice Data and their Graphical Representationp. 251
Degenerate Expectation-Maximization Algorithm for Local Dimension Reductionp. 259
A Dimension Reduction Technique for Local Linear Regressionp. 269
Reducing the Number of Variables Using Implicative Analysisp. 277
Optimal Discretization of Quantitative Attributes for Association Rulesp. 287
Part IV Symbolic Data Analysis
Clustering Methods in Symbolic Data Analysisp. 299
Dependencies in Bivariate Interval-Valued Symbolic Datap. 319
Clustering of Symbolic Objects Described by Multi-Valued and Modal Variablesp. 325
A Hausdorff Distance Between Hyper-Rectangles for Clustering Interval Datap. 333
Kolmogorov-Smirnov for Decision Trees on Interval and Histogram Variablesp. 341
Dynamic Cluster Methods for Interval Data Based on Mahalanobis Distancesp. 351
A Symbolic Model-Based Approach for Making Collaborative Group Recommendationsp. 361
Probabilistic Allocation of Aggregated Statistical Units in Classification Trees for Symbolic Class Descriptionp. 371
Building Small Scale Models of Multi-Entity Databases by Clusteringp. 381
Part V Taxonomy and Medicine
Phylogenetic Closure Operations and Homoplasy-Free Evolutionp. 395
Consensus of Classification Systems, with Adams' Results Revisitedp. 417
Symbolic Linear Regression with Taxonomiesp. 429
Determining Horizontal Gene Transfers in Species Classification: Unique Scenariop. 439
Active and Passive Learning to Explore a Complex Metabolism Data Setp. 447
Mathematical and Statistical Modeling of Acute Inflammationp. 457
Combining Functional MRI Data on Multiple Subjectsp. 469
Classifying the State of Parkinsonism by Using Electronic Force Platform Measures of Balancep. 477
Subject Filtering for Passive Biometrie Monitoringp. 485
Part VI Text Mining
Mining Massive Text Data and Developing Tracking Statisticsp. 495
Contributions of Textual Data Analysis to Text Retrievalp. 511
Automated Resolution of Noisy Bibliographic Referencesp. 521
Choosing the Right Bigrams for Information Retrievalp. 531
A Mixture Clustering Model for Pseudo Feedback in Information Retrievalp. 541
Analysis of Cross-Language Open-Ended Questions Through MFACTp. 553
Inferring User's Information Context from User Profiles and Concept Hierarchiesp. 563
Database Selection for Longer Queriesp. 575
Part VII Contingency Tables and Missing Data
An Overview of Collapsibilityp. 587
Generalized Factor Analyses for Contingency Tablesp. 597
A PLS Approach to Multiple Table Analysisp. 607
Simultaneous Row and Column Partitioning in Several Contingency Tablesp. 621
Missing Data and Imputation Methods in Partition of Variablesp. 631
The Treatment of Missing Values and its Effect on Classifier Accuracyp. 639
Clustering with Missing Values: No Imputation Requiredp. 649
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