Data Mining [ MQANT2113 ]
5.0 crédits ECTS
30.0 h + 0.0 h
1q
| Teacher(s) |
Meskens Nadine ;
|
| Language |
French
|
Place
of the course |
Mons
|
| Main themes |
- Introduction to Data Mining
- Knowledge discovery process
- Decision tree : algorithms CART and ID3
- Cross-validation, bootstrap
- Tree pruning
- bagging, boosting, arcing
- Random forest
- ROC curves
- Market basket analysis
- Neural network
- Cluster analysis : Hierarchical methods, K-means
- Rough sets
- Trends in data mining
- Software : TANAGRA et SAS enterprise Miner
- Applications
|
| Aims |
|
| Evaluation methods |
Oral examination
|
| Teaching methods |
-
Lectures
-
Course-related exercises
-
Use of software
-
Case studies
|
| Bibliography |
-
HAN J., KAMBER M. (2006), Data mining:concepts and techniques, 2nd ed.Morgan Kaufmann.
-
TUFFERY S. (2007), Data Mining et statistique décisionnelle :l'intelligence dans les bases de données, Technip.
|
Cycle et année
d'étude |
> Master [120] in Business engineering
> Master [120] in Business Engineering
|
Faculty or entity
in charge |
> BLSM
|
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