"Babes-Bolyai" University of Cluj-Napoca
Faculty of Mathematics and Computer Science
| Advanced Methods in Data Analysis |
ter |
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| Teaching Staff in Charge |
Prof. POP Horia Florin, Ph.D., hfpop cs.ubbcluj.ro |
| Aims |
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To introduce the student in advanced methods of data analysis. To offer the student the instruments that will allow him/her to develop different data analysis applications. |
| Content |
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1. Administrivia
2. Introduction to Data Mining 3. Fuzzy sets; Rough sets 4. Fuzzy logic; Fuzzy reasoning 5. Fuzzy control systems 6. Decision trees; Association rules 7. Neural networks 8. Genetic algorithms 9. Methods for prediction 10. Principal components, Factor analysis 11. Classification; Clustering 12. Feature extraction; 13. Performance analysis 14. Text mining, Web mining 15. Applications of data analysis |
| References |
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[1] A. Agresti, An Introduction to Categorical Data Analysis, Wiley, New York, 1996
[2] M. Barthold, D.J. Hand, Intelligent Data Analysis, Springer Verlag, 2003 [3] J.C. Bezdek, Pattern recognition with fuzzy objective function algorithms, Kluwer, 1981 [4] C. Bishop, Neural Networks for Pattern Recognition, Oxford University Press, 1995 [5] J. Han, M. Kamber, Data Mining: Concepts and Techniques, Academic Press, 2001 [6] G.J. Klir, B. Yuan, Fuzzy Sets and Fuzzy Logic, Prentice Hall, 1995 [7] Y.H. Pao, Adaptive pattern recognition and neural networks, Addison Wesley, 1989 [8] Statsoft inc., Electronic Statistics Textbook, Tulsa, OK, 2004, http://www.statsoft.com/textbook/stathome.html [9] Internet resources |
| Assessment |
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Each student has to prove that (s)he acquired an acceptable level of understanding and processing of the domain knowledge, that (s)he is able of expressing this knowledge in a coherent form, that (s)he has the ability to develop a conceptual analysis of the domain and to use the knowledge in problems solving. The final grade is computed as follows: 10% - Class attendance and participation; 30% - Two reports (written and presented on time); 30% - Software project (written, documented and demonstrated in time); 30% - Final exam (written paper in exams session). All elements are compulsory. |
| Links: | Syllabus for all subjects Romanian version for this subject Rtf format for this subject |