Post-Graduate Program Course: Data Mining and Soft Computing Dottorato di Ricerca in Ingegneria dell'Informazione

Francisco Herrera (Dpto. de Ciencias de la Computación e I.A.)

Summary of Sessions

Additional Slides:

• Session 0: Presentation.
• Session 1: Introduction to Data Mining and Knowledge Discovery.
• Session 2: Data Preparation.
• Session 3: Introduction to Prediction, Classification, Clustering and Association.
• Session 4: Data Mining - From the Top 10 Algorithms to the New Challenges. Part I: , Part II:
• Session 5: Introduction to Soft Computing. Focusing our attention in Fuzzy Logic and Evolutionary Computation.
• Session 6: Soft Computing Techniques in Data Mining: Fuzzy Data Mining and Knowledge Extraction based on Evolutionary Learning.
• Session 7: Genetic Fuzzy Systems: State of the Art and New Trends. Part I: , Part II: .
  • J. Alcalá-Fdez et al. (March 2008). KEEL: A Software Tool to Assess Evolutionary Algorithms for Data Mining Problems
  • H. Ishibuchi (July 2007). Multiobjective Genetic Fuzzy Systems: Review and Future Research Directions
• Session 8: Some Advanced Topics I: Classification with Imbalanced Data Sets.
• Session 9: Some Advanced Topics II: Subgroup Discovery.
• Session 10: Some advanced Topics III: Data Complexity.
• Session 11: Final talk: How must I Do my Experimental Study? Design of Experiments in Data Mining/Computational Intelligence. Using Non-parametric Tests. Some Cases of Study.

Bibliography

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	Dorian Pyle. Data Preparation for Data Mining. Morgan Kaufmann, Mar 15, 1999
	Mamdouh Refaat. Data Preparation for Data Mining Using SAS. Morgan Kaufmann, Sep. 29, 2006)
	O. Cordón, F. Herrera, F. Hoffmann, L. Magdalena. Genetic Fuzzy Systems. Evolutionary Tuning and Learning of Fuzzy Knowledge Bases, Vol. 19 of Advances in Fuzzy Systems - Applications and Theory. World Scientific, 2001 http://sci2s.ugr.es/publications/geneticFuzzySystems.php
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• T. Ho and M. Basu. Complexity measures of supervised classification problems. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(3):289–300, 2002.
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• Demsar, J., Statistical comparisons of classifiers over multiple data sets. Journal of Machine Learning Research. Vol. 7. pp. 1–30. 2006.
• S. García, D. Molina, M. Lozano, F. Herrera, A Study on the Use of Non-Parametric Tests for Analyzing the Evolutionary Algorithms' Behaviour: A Case Study on the CEC'2005 Special Session on Real Parameter Optimization. Journal of Heuristics, in press (2008),   (ENLACE ROTO)
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