Classification, Clustering, and Data Mining Applications: Proceedings of the Meeting of the International Federation of Classification Societies (IFCS), Illinois Institute of Technology, Chicago, 15–18 July 2004

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David Banks, Leanna House, Frederick R. McMorris, Phipps Arabie, Wolfgang A. Gaul
Springer Science & Business Media, Jan 7, 2011 - Language Arts & Disciplines - 658 pages
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.
 

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Contents

Thinking Ultrametrically
3
Clustering by Ant Colony Optimization
24
The Last Step of a New Divisive Monothetic Clustering
43
A SelfOrganizing Map for Dissimilarity Data
61
Controlling the Level of Separation of Components in Monte
77
Fixing Parameters in the Constrained Hierarchical
85
Spatial Pyramidal Clustering Based on a Tessellation
105
Relative Projection Pursuit and its Application
122
Phylogenetic Closure Operations and HomoplasyFree
393
Consensus of Classification Systems with Adams Results
417
Determining Horizontal Gene Transfers in Species
439
Mathematical and Statistical Modeling of Acute Inflammation
457
Classifying the State of Parkinsonism by Using Electronic
477
Subject Filtering for Passive Biometric Monitoring
485
Mining Massive Text Data and Developing Tracking Statistics
494
Contributions of Textual Data Analysis to Text Retrieval
511

Priors for Neural Networks
141
Phoneme Discrimination with Functional MultiLayer
157
On Classification and Regression Trees for Multiple Responses
177
CherryPicking as a Robustness Tool
197
Modified Biplots for Enhancing TwoClass Discriminant
233
Classification of Geospatial Lattice Data and their Graphical
250
A Dimension Reduction Technique for Local Linear
269
Optimal Discretization of Quantitative Attributes
287
Dependencies in Bivariate IntervalValued Symbolic Data
319
A Hausdorff Distance Between HyperRectangles
333
Dynamic Cluster Methods for Interval Data Based
351
Probabilistic Allocation of Aggregated Statistical Units
371
Automated Resolution of Noisy Bibliographic References
521
Choosing the Right Bigrams for Information Retrieval
531
A Mixture Clustering Model for Pseudo Feedback
541
Analysis of CrossLanguage OpenEnded Questions Through
553
Inferring Users Information Context from User Profiles
562
Database Selection for Longer Queries
575
An Overview of Collapsibility
586
Generalized Factor Analyses for Contingency Tables
597
A PLS Approach to Multiple Table Analysis
607
Simultaneous Row and Column Partitioning in Several
621
The Treatment of Missing Values and its Effect on Classifier
638
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