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
- Lectures
- Seminars
- Monday 16-18 week 1/2 - C310 - group ICA/1
- Monday 16-18 week 2/2 - C310 - group ICA/2
- Tuesday 18-20 week 2/2 - C512 - group HPC
| Week | Lectures | Seminars |
|---|
| 1 | Administrivia, Introduction | No physical classes.
Time allocated for
individual study |
|---|
| 2 | Fuzzy sets, Fuzzy logic |
|---|
| 3 | Fuzzy reasoning, Fuzzy control systems
Fuzzy clustering |
|---|
| 4 | Fuzzy clustering, Quality measures, SOM, MDS |
|---|
| 5 | PCA, Discriminant analysis, Regression
Rough sets, Association rules
|
|---|
| 6 | Applications of data analysis and fuzzy sets |
|---|
| Week | Class presentations |
|---|
| 7 | First report |
|---|
| 8 |
|---|
| 9 |
|---|
| 10 |
|---|
| 11 | Second report |
|---|
| 12 |
|---|
| 13 |
|---|
| 14 |
|---|
4. Online resources
- Lecture notes and other resources are available on the UBB Sharepoint platform.
- Please understand that the lecture notes will be posted here AFTER the class.
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 - Theoretical
- deadline for setting the title and slot = week 5 (class day)
- class presentations = week 7, week 8, week 9, week 10
- the reports presentation schedule is published and updated on the UBB Sharepoint platform
Second report - Experimental
- deadline for setting the title = week 9 (class day)
- class presentations = week 11, week 12, week 13, week 14
- the reports presentation schedule is published and updated on the UBB Sharepoint platform
6. Bibliography
- J. Han, M. Kamber, Data Mining: Concepts and Techniques, Academic Press, 2001
- G.J. Klir, B. Yuan, Fuzzy Sets and Fuzzy Logic, Prentice Hall, 1995
- T. Mitchell, Machine Learning, McGraw Hill, 1996
- Z. Pawlak, Rough Sets, Polish Academy of Sciences, Gliwice, 2004
- N. Ye, The Handbook of Data Mining, Lawrence Elbaum Associates Publishers, 2003
Optional bibliography
- A. Agresti, An Introduction to Categorical Data Analysis, Wiley, New York, 1996
- M. Barthold, D.J. Hand, Intelligent Data Analysis, Springer Verlag, 2003
- J.C. Bezdek, Pattern Recognition with Fuzzy Objective Function Algoritms, Plenum Press, New York, 1981
- C. Bishop, Neural Networks for Pattern Recognition, Oxford University Press, 1995
- Y.H. Pao, Adaptive pattern recognition and neural networks, Addison Wesley, 1989
- Statsoft inc., Electronic Statistics Textbook, Tulsa, OK, 2006, Website
- Open internet resources
© Prof.dr. Horia F. Pop