Advances in Data Analysis, Data Handling and Business Intelligence

Proceedings of the 32nd Annual Conference of the Gesellschaft für Klassifikation e.V., Joint Conference with the British Classification Society (BCS) and the Dutch/Flemish Classification Society (VOC), Helmut-Schmidt-University, Hamburg, July 16-18, 2008

Editors:

ISBN: 978-3-642-01043-9 (Print) 978-3-642-01044-6 (Online)

Table of contents (71 chapters)

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  1. Front Matter

    Pages 1-23

  2. Invited

    1. Front Matter

      Pages 1-1

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      Pages 3-20

      Semi-supervised Probabilistic Distance Clustering and the Uncertainty of Classification

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      Pages 21-32

      Strategies of Model Construction for the Analysis of Judgment Data

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      Pages 33-44

      Clustering of High-Dimensional Data via Finite Mixture Models

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      Pages 45-55

      Clustering and Dimensionality Reduction to Discover Interesting Patterns in Binary Data

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      Pages 57-66

      Kernel Methods for Detecting the Direction of Time Series

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      Pages 67-79

      Statistical Processes Under Change: Enhancing Data Quality with Pretests

  3. Clustering and Classification

    1. Front Matter

      Pages 82-82

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      Pages 83-92

      Evaluation Strategies for Learning Algorithms of Hierarchies

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      Pages 93-103

      Fuzzy Subspace Clustering

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      Pages 105-114

      Motif-Based Classification of Time Series with Bayesian Networks and SVMs

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      Pages 115-125

      A Novel Approach to Construct Discrete Support Vector Machine Classifiers

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      Pages 127-134

      Predictive Classification Trees

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      Pages 135-145

      Isolated Vertices in Random Intersection Graphs

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      Pages 147-156

      Strengths and Weaknesses of Ant Colony Clustering

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      Pages 157-166

      Variable Selection for Kernel Classifiers: A Feature-to-Input Space Approach

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      Pages 167-176

      Finite Mixture and Genetic Algorithm Segmentation in Partial Least Squares Path Modeling: Identification of Multiple Segments in Complex Path Models

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      Pages 177-184

      Cluster Ensemble Based on Co-occurrence Data

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      Pages 185-195

      Localized Logistic Regression for Categorical Influential Factors

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      Pages 197-205

      Clustering Association Rules with Fuzzy Concepts

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      Pages 207-215

      Clustering with Repulsive Prototypes

  4. Mixture Analysis

    1. Front Matter

      Pages 218-218

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      Pages 219-228

      Weakly Homoscedastic Constraints for Mixtures of t-Distributions

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