Advanced Methods in Data Analysis (2024-2025)

Requirements

Grading scheme

Code of conduct

The final exam

1. Instructor

Prof.dr. Horia F. Pop, Email:

2. Preliminaries

This is a research oriented class. Your grade will be based on your own work and on your understanding of it, including your ability to explain, defend and analyse your work and your results.

3. Schedule of activities

 

WeekLecturesSeminars
1Administrivia, Introduction to Data Analysis
2Fuzzy sets, Fuzzy logic 
3Fuzzy reasoning, Fuzzy control systems, Fuzzy clustering
4Quality measures, PCA, Discriminant analysis, Regression
5Rough sets, Decision tables, Association rules
6Applications of data analysis and fuzzy sets
7Report 1Report 1
8
9
10
11Report 2Report 2
12
13
14

4. Online resources

5. Students deliverables

You will work on your own preferred research topics. They have to be relevant to the general class topic (i.e. Data Analysis), but do not need to refer strictly to topics from the lectures.

First report

Second report

6. Bibliography

  1. J. Han, M. Kamber, Data Mining: Concepts and Techniques, Academic Press, 2001
  2. G.J. Klir, B. Yuan, Fuzzy Sets and Fuzzy Logic, Prentice Hall, 1995
  3. T. Mitchell, Machine Learning, McGraw Hill, 1996
  4. Z. Pawlak, Rough Sets, Polish Academy of Sciences, Gliwice, 2004
  5. N. Ye, The Handbook of Data Mining, Lawrence Elbaum Associates Publishers, 2003

Optional bibliography

  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 Algoritms, Plenum Press, New York, 1981
  4. C. Bishop, Neural Networks for Pattern Recognition, Oxford University Press, 1995
  5. Y.H. Pao, Adaptive pattern recognition and neural networks, Addison Wesley, 1989
  6. Statsoft inc., Electronic Statistics Textbook, Tulsa, OK, 2006, Website
  7. Open internet resources

© Prof.dr. Horia F. Pop