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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
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
Original Title
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
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, 2008Author: Andreas Fink, Berthold Lausen, Wilfried Seidel, Alfred Ultsch Published by Springer Berlin Heidelberg ISBN: 978-3-642-01043-9 DOI: 10.1007/978-3-642-01044-6Table of Contents:Semi-supervised Probabilistic Distance Clustering and the Uncertainty of Classification
Strategies of Model Construction for the Analysis of Judgment Data
Clustering of High-Dimensional Data via Finite Mixture Models
Clustering and Dimensionality Reduction to Discover Interesting Patterns in Binary Data
Kernel Methods for Detecting the Direction of Time Series
Statistical Processes Under Change: Enhancing Data Quality with Pretests
Evaluation Strategies for Learning Algorithms of Hierarchies
Fuzzy Subspace Clustering
Motif-Based Classification of Time Series with Bayesian Networks and SVMs
A Novel Approach to Construct Discrete Support Vector Machine Classifiers
Predictive Classification Trees
Isolated Vertices in Random Intersection Graphs
Strengths and Weaknesses of Ant Colony Clustering
Variable Selection for Kernel Classifiers: A Feature-to-Input Space Approach
Finite Mixture and Genetic Algorithm Segmentation in Partial Least Squares Path Modeling: Identification of Multiple Segments in Complex Path Models
Cluster Ensemble Based on Co-occurrence Data
Localized Logistic Regression for Categorical Influential Factors
Clustering Association Rules with Fuzzy Concepts
Clustering with Repulsive Prototypes
Weakly Homoscedastic Constraints for Mixtures of t-DistributionsIncludes bibliographical references and indexes
