Titlebook: Classification and Knowledge Organization; Proceedings of the 2 Rüdiger Klar,Otto Opitz (Lehrstuhl für Mathematisc Conference proceedings 1

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Rüdiger Klar,Otto Opitz (Lehrstuhl für Mathematisc

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High Dimensional Clustering Using Parallel Coordinates and the Grand Touronal plots allowed by the parallel coordinate display, these techniques allow the data analyst to explore data which is both high-dimensional and massive in size. In this paper we give a description of both techniques and illustrate their use to do inverse regression and clustering. We have used the

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Fixed Point Clusters and Their Relation to Stochastic Modelsng of a statistical parameter estimation and a classification of data in “near” and “outlying” with respect to the estimator. The relation of Fixed Point Clustering to parameter estimation in stochastic models will be discussed. FPCs use stochastic models as orientation rather than as basis. They ar

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Recent Developments in Three-Way Data Analysis: A Showcase of Methods and Examplestion will be followed by a scheme presenting an indication of the techniques involved. Then four condensed examples will give a feel of the scope of applications, while the final section is devoted to publicly available programs to perform the analyses.

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A Hybrid Global Optimization Algorithm for Multidimensional Scaling if the underlying dissimilarity matrix is far from being Euclidean. However, in order to remove ambiguity from the model building process, it is of paramount interest to fit a suggested model best to a given data set. Hence, finding the global minimum of STRESS is very important for applications of

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