Opinto-opas 2005-2006

SGN-5306 KNOWLEDGE MINING, 3 cr
KNOWLEDGE MINING

Person responsible
Professor Ari Visa

Lecturers
Ari Visa, Professor, room TF309, ari.visa@tut.fi

Implementation rounds
Implementation 1
  Period 1 Period 2 Period 3 Period 4 Period 5 Summer Language of instruction
Lecture - - - 4 h/week - - In English only
Exercise - - - 4 h/week - - In English only
Exam   In finnish and in english if asked
(Academic Calender 2005-2006)

Objectives
The course equips the student with a sound understanding of data mining methods for data mining principles and makes it possible for students to teaches methods for knowledge discovery in large corporate databases.

Contents
Content Core content Complementary knowledge Specialist knowledge
1. Concept Description  Data preprocessing
Data Generalization
Summarization-Based Characterization
Analyzing of Attribute Relevance 		   
2. Mining Association Rules  Mining Single-Dimensional Boolean Association Rules, and Multilevel Association Rules, and Multidimensional Association Rules
Correlation Analysis
 		   
3. Descriptive Models  Cluster Analysis
Describing Data by Probability Distributions and Densities
 		 Parametric models
Nonparametric models 
4. Predictive Models  Regression models
Stochastic models
Predictive models for classification
Models for structured data 		   

Requirements for completing the course
Project work and final examination.

Assessment criteria
The examination is based on the final exam and an exercise work. The grading of the execise work is pass/fail.

  • Used assessment scale is numeric (1-5)

    • Study material
    Type Name Author ISBN URL, edition, availablitity... Exam material Language
    Book "Data Mining: Concepts and Techniques" Jiawei Han & Micheline Kamber   Morgan Kaufmann Publisher, 2000 Yes  English 
    Book "Principles of Data Mining" David J. Hand, Heikki Mannila and Padhraic Smyth   MIT Press, 2000 Yes  English 

    Prerequisites
    Number Name Credits M/R
    OHJ-1100 Programming I 4 Mandatory
    OHJ-1106 Programming I 4 Mandatory
    OHJ-1150 Programming II 5 Mandatory
    OHJ-1156 Programming II 5 Mandatory
    SGN-1106 Introductory Signal Processing 3 Recommendable
    SGN-1200 Signal Processing Methods 4 Recommendable
    SGN-1250 Signal Processing Applications 4 Recommendable

    Additional information related to prequisites
    Basic programming skills are required.

    Other comments
    Lectures in English or in Finnish.

  • Partial passing of course must be in connection with the same round of implementation.
  • The course is suitable for postgraduate studies.
  • Course will not be lectured in the academic year 2005-2006.

    • Correspondence of content
    8004202 Data Mining

    Course homepage

    Last modified 17.02.2005
    Modified byAntti Niemistö