From Data and Information Analysis to Knowledge Engineering by Myra Spiliopoulou, Rudolf Kruse, Christian Borgelt, Andreas

By Myra Spiliopoulou, Rudolf Kruse, Christian Borgelt, Andreas Nurnberger, Wolfgang Gaul (Editors)

The amount includes revised types of chosen papers awarded through the twenty ninth Annual convention of the Gesellschaft f?r Klassifikation (GfKl), the German class Society, held on the Otto-von-Guericke-University of Magdeburg, Germany, in March 2005. as well as papers at the conventional matters category, Clustering, and information research, there are various papers on a variety of subject matters with a robust relation to computing device technological know-how. Examples are textual content Mining, net Mining, Fuzzy information research, IT defense, Adaptivity and Personalization, and Visualization. Application-oriented issues comprise Economics, advertising, Banking and Finance, medication, Bioinformatics, Biostatistics, and song research.

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J. (1998): UCI repository of machine learning databases. html. M. (2005): Swarm based fuzzy clustering with partition validity. Proc. 14th IEEE Int. Conf. on Fuzzy Systems (FUZZ-IEEE’05). IEEE Press, Piscataway, NJ. To Appear. , and DORIGO, M. (2003a): On the performance of antbased clustering. design and application of hybrid intelligent systems. Frontiers in Artificial intelligence and Applications 104, 204–213. , and DORIGO, M. (2003b): Strategies for the increased robustness of ant-based clustering.

28, 337–407 (with discussion). GREENSHTEIN, E. and RITOV, Y. (2004): Persistency in high dimensional linear predictor-selection and the virtue of over-parametrization. Bernoulli, 10, 971– 988. JIANG, W. (2004): Process consistency for AdaBoost. Ann. , 32, 13–29 (disc. pp. 85–134). MALLAT, S and ZHANG, Z. (1993): Matching pursuits with time-frequency dictionaries. IEEE Trans. , 41, 3397–3415. ¨ MEINSHAUSEN, N. and BUHLMANN, P. (2004): High-dimensional graphs and variable selection with the Lasso.

And BATOUCHE, M. (2002): Unsupervised image segmentation using a colony of cooperating ants. Biologically Motivated Computer Vision, 2nd Int. Workshop, BMCV 2002, LNCS 2525, 109–116. Springer-Verlag, Berlin. C. (1995): On cluster validity for the fuzzy c-means model. IEEE Trans. on Fuzzy Systems, 3(3):370–379. ULTSCH, A. (2004): Strategies for an artificial life system to cluster high dimensional data. Abstracting and Synthesizing the Principles of Living Systems, GWAL-6, 128–137. A. (1991): Validity measure for fuzzy clustering.

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