DATA MINING COURSES

Data mining
Vietnam national university in Hanoi,
College of technology, Feb.2006

Rough sets in Data Mining
Vietnam national university in Hanoi,
College of technology, Feb.2006

1. Introduction to KDD and data mining; templates and patterns
2. Transaction data analysis and association rules; main algorithms for association rule generation: Apriori, AprioriTid, FP-tree.
3. Classification problem, case based methods, naïve Bayes classifiers, Bayesian networks.
4. Data cleaning and data preprocessing techniques;
5. Decision trees;
6. Rule based classifiers;
7. Classifier evaluation methods;
8. Clustering problem and clustering algorithms
9. Searching for sequence patterns from time series data
10. Summary

1. Introduction: Data mining and rough set theory (RSDM1)
2. Boolean reasoning approach to rough set and data mining (RSDM2)
3. Rough sets approach to feature selection problem & decision rules (DM6 and RSDM2)
4. Rough sets and association rules (DM2 and RSDM2)
5. Rough sets in data preprocessing (discretization of real value attributes)(RSDM3 and DM4)
6. Computational learning theorem (RSDM4)
7. Rough sets in decision trees and rough set methods for large data sets (RSDM5 and DM5)
8. Rough sets and layered learning.
9. Summary