Artificial Intelligence and Innovations 2007: from Theory to by Ioannis T. Christou, Sofoklis Efremidis (auth.), Christos

By Ioannis T. Christou, Sofoklis Efremidis (auth.), Christos Boukis, Aristodemos Pnevmatikakis, Lazaros Polymenakos (eds.)

International Federation for info Processing

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2002), SMOTE: Synthetic Minority Over-sampling Technique, Journal of Artificial Intelligence Research 16, 321 - 357. 4. Domingos P. (1998), How to get a free lunch: A simple cost model for machine learning appHcations. Proc. AAAI-98/ICML98, Workshop on the Methodology of Applying Machine Learning, ppl-7. 5. Domingos P. & Pazzani M. (1997). On the optimality of the simple Bayesian classifier under zero-one loss. Machine Learning, 29,103-130. 6. Domingos, P. (1999). MetaCost: A General Method for Making Classifiers CostSensitive.

Preventing student dropout in distance learning systems using machine learning techniques, LNAI, Vol 2774, pp 267-274, 2003 11. , Kanellopoulos, D. Pintelas, P. 30 (1), pp. 25-36. 12. , Holte, R. and Matwin, S. (1998), 'Machine Learning for the Detection of Oil Spills in Radar Images', Machine Learning, 30:195-215. 13. Ling, C, & Li, C. (1998). Data Mining for Direct Marketing Problems and Solutions. In Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98) New York, NY.

Visualization and Grouping of Graph Patterns in Molecular Databases, Submitted. 2. , Bork, P. : Self-Organizing Hierarchic Networks for Pattern Recognition in Protein Sequences, Protein Science Journal 5 (1996), pp. 72-82. 3. J. : Self-Organizing Maps of Position Weight Matrices for Motif Discovery in Biological Sequences, Artificial Intelligence Review Journal 24 (2005), pp. 397-413. 4. N. : Reliable Hierarchical Clustering with the Self-Organizing Map, in Proc. 6th International Symposium on Intelligent Data Analysis (IDA 2005), LNCS 2810, pp.

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