By Juan M. Corchado, M. Lourdes Borrajo, María A. Pellicer, J. Carlos Yáñez (auth.), Petra Perner (eds.)
The business convention on info Mining ICDM-Leipzig was once the fourth assembly in a sequence of annual occasions which begun in 2000, geared up by way of the Institute of computing device imaginative and prescient and utilized desktop Sciences (IBaI) in Leipzig. The challenge of the convention is to compile researchers and other people from in an effort to talk about jointly new tendencies and purposes in facts mining. This yr a extensive spectrum of labor of alternative functions was once offered starting from picture mining, medication and biotechnology, administration and environmental keep watch over, to telecommunications. along with that an business exhibition confirmed the profitable software of information mining tools through industries in several parts akin to scientific units, mass info administration platforms, facts mining instruments, and so on. through the dialogue many tasks have been encouraged resulting in new and joint paintings. The fruitful discussions, the alternate of principles and the spirit of the convention made it a outstanding occasion for each side, and learn. we wish to precise our appreciation to the reviewers for his or her distinct and hugely specialist paintings. We enjoy the assistance and figuring out of the editorial employees at Springer and specifically Alfred Hofmann, who supported the e-book of those court cases within the LNAI sequence. final, yet now not least, we want to thank all audio system, members and business exhibitors who contributed to the good fortune of the convention. we're looking ahead to welcoming you to ICDM 2005 (www.data-mini- forum.de) and to the hot paintings you are going to current there.
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Additional info for Advances in Data Mining: Applications in Image Mining, Medicine and Biotechnology, Management and Environmental Control, and Telecommunications; 4th Industrial Conference on Data Mining, ICDM 2004, Leipzig, Germany, July 4 -7, 2004, Revised Selected Paper
The components of the vector x are called the features. Given feature vector can contain the numerical results of the fixed set of n measurements on particular object Let the symbol mean the feature vector assigned (labelled) to the k-th class The assignment of the feature vectors (j =1,….. ,m) from the database to particular categories is performed by applying some additional (expert) information. The learning set contains feature vectors labelled to the same class where is the set of indices j of the feature vectors belonging to the class In accordance with the K-NN rule a new object is allocated to this category to which most of the K nearest neighbours of the vector belong, where vector represents a new object.
E. Hart, D. G. Stork: Pattern Classification, J. Wiley, New York, 2001. 2. K. , San Diego, 1990. 3. J. L. Kolodner: Case-based Reasoning, Morgan Kaufmann, San Mateo, CA 1993. 4. P. Perner, Data Mining on Multimedia Data, Springer, Berlin 2002 5. R. A. Johnson, D. W. , Englewood Cliffs, New York, 1991 6. L. Bobrowski, M. Topczewska: “Tuning of diagnosis support rules through visualizing data transformations”, pp. 15-23 in Medical Data Analysis, P. , Springer-Verlag Berlin , Heidelberg 2003 7. L.
These are some of the problems that have to be solved in the framework of this project. Table 3 also shows the generalization capabilities of the proposed model, since it is even able to generate reasonable results in an extended area, when the instance-base has only been constructed with data from one part of the area. References 1. Corchado E. and Fyfe C. (2003) Orientation Selection Using Maximum Likelihood Hebbian Learning, International Journal of Knowledge-Based Intelligent Engineering Systems Volume 7 Number 2, April 2003.
Advances in Data Mining: Applications in Image Mining, Medicine and Biotechnology, Management and Environmental Control, and Telecommunications; 4th Industrial Conference on Data Mining, ICDM 2004, Leipzig, Germany, July 4 -7, 2004, Revised Selected Paper by Juan M. Corchado, M. Lourdes Borrajo, María A. Pellicer, J. Carlos Yáñez (auth.), Petra Perner (eds.)