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Data Mining: Concepts and TechniquesFDA140, 2003VTFull
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Course plan
No of lectures
36 hours
Recommended for
The course was last given
Never given before
Goals
The goal of the course is to provide in depth, rigorous overview of all
essencial methods and techniques involved in the process of Knowledge
Discovery in Databases (KDD). The KDD process consists of an interactive
sequence of following steps; data cleaning, data integration, data selection,
data transformation, data mining, pattern evaluation, and knowledge
representation.
Data Mining is KDD essential step where intelligent methods are applied in
order to extract data patterns. We will discuss all types of knowledge types
(patterns) to be mined and all relevant methods and algorithms involved as well
as primitives of Data Mining systems architecture and design.
We will also explore the newest trends and developements of the field in form
of students talks based on research papers and applications.
Prerequisites
Introductory database course.
Organization
Contents
In particular we will cover the following subjects.
1.General overview:
what is Data Mining, which data, what kinds of patterns
can be mined.
2. Data Warehouse and OLAP technology
for Data Mining.
3. Data preprocessing: data cleaning, data integration and
transformation, data reduction, discretization
and concept hierachy generation.
4. Data Mining Primitives, Languages and System
Archtectures.
5. Mining Association Rules in Large Databases.
Transactional databases and Apriori Algorithm.
6. Classification and prediction. Classifiers:
ID3, C4.5, Neural Networks, Rough Sets, Fuzzy sets,
Bayesian belief networks, genetic algorithms.
Statistical Prediction.
7. Cluster Analysis.
A Categorization of major Clustering methods.
Literature
DATA MINING Concepts and Techniques
Jiawei Han, Micheline Kamber
Morgan Kaufman Publishers, 2001.
Lecturers
Professor Anita Wasilewska
Examiner
Ulf Nilsson
Examination
In class presentation and final paper.
Credit
5 credits
Comments
Crash course.
Page responsible: Director of Graduate Studies
